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4. The method of claim 3 wherein combining includes only combining those identified self-describing fragments that have corresponding portion of the input text that do not overlap.
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4. The method of claim 3 wherein combining includes only combining those identified self-describing fragments that have corresponding portion of the input text that do not overlap. 5. The method of claim 4 wherein combining includes only combining those identified self-describing fragments that are unique from each other.
| 0.929427 |
12. A user device arranged to obtain user feedback relating to items displayable by the device, the device comprising: a display; and a display control arrangement for displaying on the display a view of a said displayable item, a first activatable transport-control element with associated first semantic information that is indicative of a user's experience in respect of a displayed item, and a second activatable transport-control element with associated second semantic information that is indicative of a user's experience in respect of a displayed item and is different from said first semantic information; the control arrangement being arranged to respond to user activation of a said transport-control element both by moving the displayed item view within or between displayable items and by storing or outputting data indicative of the semantic information associated with the activated element, the item-view move that is effected as a result of activation of a said transport-control element being the same whichever of said elements is activated.
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12. A user device arranged to obtain user feedback relating to items displayable by the device, the device comprising: a display; and a display control arrangement for displaying on the display a view of a said displayable item, a first activatable transport-control element with associated first semantic information that is indicative of a user's experience in respect of a displayed item, and a second activatable transport-control element with associated second semantic information that is indicative of a user's experience in respect of a displayed item and is different from said first semantic information; the control arrangement being arranged to respond to user activation of a said transport-control element both by moving the displayed item view within or between displayable items and by storing or outputting data indicative of the semantic information associated with the activated element, the item-view move that is effected as a result of activation of a said transport-control element being the same whichever of said elements is activated. 23. A device according to claim 12 , wherein said information describing a user's experience is selected from the set comprised of: information determining whether a user found/did not find what-they wanted; information describing whether a user had a good/bad experience; and information describing whether a user had a satisfactory/unsatisfactory experience.
| 0.5 |
27. A system for detecting a malicious program comprising: at least one computer; a sensor installed on the at least one computer, the sensor structured and arranged to collect information on resource utilization of the at least one computer; and a machine learning daemon structured and arranged to receive bundles of information from the sensor and determine a probability that the computer is infected with a malicious program, wherein the sensor and machine learning daemon are structured and arranged to: randomly sample a trace of system calls collected over a predetermined interval, each system call including context information and memory addresses for a function being monitored; compute system address differences from the trace of system calls and retaining computed values; form a group of n-grams (words) of retained differences of system addresses from the trace of system calls; form a series of process snippets, each process snippet including the context information and the retained differences of system addresses; transform each process snippet to form a compact representation (process dot) comprising a pair of elements (c, a), wherein c includes the context information and a is a sparse vector that encodes information derived from the group of n-grams; form clusters of compact representations; and compare the clusters formed to a library of malicious program samples.
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27. A system for detecting a malicious program comprising: at least one computer; a sensor installed on the at least one computer, the sensor structured and arranged to collect information on resource utilization of the at least one computer; and a machine learning daemon structured and arranged to receive bundles of information from the sensor and determine a probability that the computer is infected with a malicious program, wherein the sensor and machine learning daemon are structured and arranged to: randomly sample a trace of system calls collected over a predetermined interval, each system call including context information and memory addresses for a function being monitored; compute system address differences from the trace of system calls and retaining computed values; form a group of n-grams (words) of retained differences of system addresses from the trace of system calls; form a series of process snippets, each process snippet including the context information and the retained differences of system addresses; transform each process snippet to form a compact representation (process dot) comprising a pair of elements (c, a), wherein c includes the context information and a is a sparse vector that encodes information derived from the group of n-grams; form clusters of compact representations; and compare the clusters formed to a library of malicious program samples. 29. The system of claim 27 , wherein there is a waiting period chosen from a random exponential distribution before repeating the steps of claim 27 .
| 0.530646 |
12. The machine-readable medium of claim 10 , the process further comprising: sorting the candidate routes based on their scores; wherein providing at least one scored route to the user includes providing a plurality of high scoring routes for user selection.
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12. The machine-readable medium of claim 10 , the process further comprising: sorting the candidate routes based on their scores; wherein providing at least one scored route to the user includes providing a plurality of high scoring routes for user selection. 13. The machine-readable medium of claim 12 , the process further comprising: receiving a selected route from the user; and determining if the attribute weights need to be adjusted based on that user selection.
| 0.936924 |
13. A method for assisting an agent in a contact center in responding to an enquiry of a caller comprising: receiving an incoming voice call from the caller at the contact center; answering the incoming voice call by an interactive voice response unit (“IVR”) of the contact center; place the voice call in a hold queue, playing a first announcement to the caller indicating the incoming voice call is in the hold queue, ascertaining the incoming voice call originated from a wireless telephone number, in response to ascertaining the incoming voice call originated from the wireless telephone number, playing a second announcement to the caller requesting a voice message be left by the caller in expectation of receiving a subsequent communication comprising a short message service (“SMS”) text message responding to the voice message; receiving the voice message from the caller; storing the voice message in a memory store; processing the voice message from the caller to identify one or more keywords in speech from the caller; determining an agent is available to provide the subsequent communication to the caller; presenting the agent with information related to the voice message including a transcript of the voice message; displaying an icon to the agent for playing audio of the voice message; receiving a selection of the icon from the agent for playing the audio of the voice message; in response to receiving the selection of the icon, playing the audio of the voice message to the agent; and presenting information on a monitor of a computer used by the agent, wherein the information relates to the subsequent communication to be conveyed to the caller.
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13. A method for assisting an agent in a contact center in responding to an enquiry of a caller comprising: receiving an incoming voice call from the caller at the contact center; answering the incoming voice call by an interactive voice response unit (“IVR”) of the contact center; place the voice call in a hold queue, playing a first announcement to the caller indicating the incoming voice call is in the hold queue, ascertaining the incoming voice call originated from a wireless telephone number, in response to ascertaining the incoming voice call originated from the wireless telephone number, playing a second announcement to the caller requesting a voice message be left by the caller in expectation of receiving a subsequent communication comprising a short message service (“SMS”) text message responding to the voice message; receiving the voice message from the caller; storing the voice message in a memory store; processing the voice message from the caller to identify one or more keywords in speech from the caller; determining an agent is available to provide the subsequent communication to the caller; presenting the agent with information related to the voice message including a transcript of the voice message; displaying an icon to the agent for playing audio of the voice message; receiving a selection of the icon from the agent for playing the audio of the voice message; in response to receiving the selection of the icon, playing the audio of the voice message to the agent; and presenting information on a monitor of a computer used by the agent, wherein the information relates to the subsequent communication to be conveyed to the caller. 14. The method of claim 13 , wherein the information related to the voice message comprises a draft SMS text message, and the method further comprises: receiving an input from the agent editing the draft SMS text message thereby generating a final SMS text message; and sending the final SMS text message as the subsequent communication to a wireless number associated with the voice call from the caller.
| 0.590711 |
1. A method comprising: recognizing speech received from a plurality of speakers to yield recognized speech for each of the speakers, wherein each speaker in the plurality of speakers interacts with a speech interface that uses a set of allocated resources comprising a first resource and a second resource that is associated with the each speaker in the plurality of speakers, and wherein the set of allocated resources comprise at least one of bandwidth and processor time; recording metrics associated with the recognized speech for each of the plurality of speakers, wherein the metrics comprise a speech recognition confidence score, a processing speed, a dialog behavior, a request for repetition, a negative response to confirmation, and a task completion; after recording the metrics, while recording further speech from each speaker in the plurality of speakers, modifying at least one of the first resource and the second resource commensurate with the metrics, to yield a modified set of allocated resources; and recognizing additional speech during a conference call from an identified speaker in the plurality of speakers using the modified set of allocated resources for speakers predetermined to be frustrated and have great difficulty in a prior session.
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1. A method comprising: recognizing speech received from a plurality of speakers to yield recognized speech for each of the speakers, wherein each speaker in the plurality of speakers interacts with a speech interface that uses a set of allocated resources comprising a first resource and a second resource that is associated with the each speaker in the plurality of speakers, and wherein the set of allocated resources comprise at least one of bandwidth and processor time; recording metrics associated with the recognized speech for each of the plurality of speakers, wherein the metrics comprise a speech recognition confidence score, a processing speed, a dialog behavior, a request for repetition, a negative response to confirmation, and a task completion; after recording the metrics, while recording further speech from each speaker in the plurality of speakers, modifying at least one of the first resource and the second resource commensurate with the metrics, to yield a modified set of allocated resources; and recognizing additional speech during a conference call from an identified speaker in the plurality of speakers using the modified set of allocated resources for speakers predetermined to be frustrated and have great difficulty in a prior session. 8. The method of claim 1 , further comprising progressively applying the modified set of allocated resources.
| 0.610115 |
8. A server having at least one processor, storage, and a communication platform connected to a network, the server comprising: a query processor configured for receiving, at the server, a search query from a user that was sent using a client device, and for determining information for the user that is associated with the search query, wherein the information for the user includes information about a location; a general search engine configured for performing a search, in a general subdomain, and identifying general content based on the search query; a plurality of vertical search engines comprising a vertical search engine configured for performing a search, in a vertical subdomain, and identifying specialized content based on the search query, wherein the vertical subdomain is selected based on the location in the information for the user, wherein the vertical search engine is controlled by an owner of the general search engine; and a page constructor configured for providing both the specialized content and the general content as a response to the search query.
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8. A server having at least one processor, storage, and a communication platform connected to a network, the server comprising: a query processor configured for receiving, at the server, a search query from a user that was sent using a client device, and for determining information for the user that is associated with the search query, wherein the information for the user includes information about a location; a general search engine configured for performing a search, in a general subdomain, and identifying general content based on the search query; a plurality of vertical search engines comprising a vertical search engine configured for performing a search, in a vertical subdomain, and identifying specialized content based on the search query, wherein the vertical subdomain is selected based on the location in the information for the user, wherein the vertical search engine is controlled by an owner of the general search engine; and a page constructor configured for providing both the specialized content and the general content as a response to the search query. 14. The server of claim 8 , wherein the page constructor is further configured for providing information identifying the vertical subdomain comprising the specialized content identified based on the search query.
| 0.616169 |
10. A set of instructions embodied and stored in a non-transitory computer-storage medium, which when executed by one or more processors perform operations for providing query parameters to a search engine, comprising: receiving a selection that includes at least two locations of a graphical user interface, wherein the at least two locations define an area of the graphical user interface that has been selected by a user of a computing device; identifying one or more selected elements of a graphical user interface that are contained within the defined area of the graphical user interface, wherein the one or more selected elements are unable to receive information from the user; converting the one or more selected elements into selected textual search data at a time subsequent to the definition of the selected area; determining that the one or more selected elements comprise a partial word; identifying one or more unselected elements of the graphical user interface that the user did not select, wherein the one or more unselected elements are identified from among a plurality of unselected elements that are located outside of the defined area of the graphical user interface based on a determination that the one or more unselected elements, when appended to the one or more selected elements, will complete the partial word; appending unselected textual search data associated with the one or more unselected elements to the selected textual search data of the one or more selected elements; determining a context associated with the one or more selected elements based on the identified one or more unselected elements; generating one or more query terms based on the determined context, wherein the one or more query terms are different than the unselected textual search data; creating a search engine query based on the selected textual search data appended with the unselected textual search data and the one or more query terms; and initiating a search of stored data based on the created search engine query.
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10. A set of instructions embodied and stored in a non-transitory computer-storage medium, which when executed by one or more processors perform operations for providing query parameters to a search engine, comprising: receiving a selection that includes at least two locations of a graphical user interface, wherein the at least two locations define an area of the graphical user interface that has been selected by a user of a computing device; identifying one or more selected elements of a graphical user interface that are contained within the defined area of the graphical user interface, wherein the one or more selected elements are unable to receive information from the user; converting the one or more selected elements into selected textual search data at a time subsequent to the definition of the selected area; determining that the one or more selected elements comprise a partial word; identifying one or more unselected elements of the graphical user interface that the user did not select, wherein the one or more unselected elements are identified from among a plurality of unselected elements that are located outside of the defined area of the graphical user interface based on a determination that the one or more unselected elements, when appended to the one or more selected elements, will complete the partial word; appending unselected textual search data associated with the one or more unselected elements to the selected textual search data of the one or more selected elements; determining a context associated with the one or more selected elements based on the identified one or more unselected elements; generating one or more query terms based on the determined context, wherein the one or more query terms are different than the unselected textual search data; creating a search engine query based on the selected textual search data appended with the unselected textual search data and the one or more query terms; and initiating a search of stored data based on the created search engine query. 11. The medium of claim 10 , wherein the operations are performed in response to a single mouse click.
| 0.570313 |
1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets.
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1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets. 3. The system of claim 1 , comprising generating histogram-based features in a graph-based hierarchical segmentation.
| 0.573789 |
1. A method for generating speech based on text in one or more languages, implemented at least in part by a computer, the method comprising: providing a phone set for a plurality of languages, the phone set comprising a union of phones of the plurality of languages; training, for the plurality of languages, a multilingual hidden Markov model (HMM) comprising state level sharing across the plurality of languages based on language sentences in each of the plurality of languages without any sentences including a mixture of more than one language; tying states of the multilingual HMM across the plurality of languages and clustering the tied states across the plurality of languages into a single decision based at least in part on a language independent question and a language specific question; receiving text in one or more of the plurality of languages of the multilingual HMM; and generating speech, for the received text, based at least in part on the multilingual HMM.
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1. A method for generating speech based on text in one or more languages, implemented at least in part by a computer, the method comprising: providing a phone set for a plurality of languages, the phone set comprising a union of phones of the plurality of languages; training, for the plurality of languages, a multilingual hidden Markov model (HMM) comprising state level sharing across the plurality of languages based on language sentences in each of the plurality of languages without any sentences including a mixture of more than one language; tying states of the multilingual HMM across the plurality of languages and clustering the tied states across the plurality of languages into a single decision based at least in part on a language independent question and a language specific question; receiving text in one or more of the plurality of languages of the multilingual HMM; and generating speech, for the received text, based at least in part on the multilingual HMM. 2. The method of claim 1 wherein the plurality of languages comprise English and/or Mandarin.
| 0.591723 |
1. A search engine server comprising: one or more processors; and one or more computer storage media storing computing-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive, at the search engine server from an end user computing device, a plurality of content signatures of a web page, the plurality of content signatures having been automatically generated at the end user computing device from content of the web page downloaded and displayed by the end user computing device, the web page having been downloaded by the end user computing device from one or more content servers separate from the search engine server when an end user employed the end user computing device to access the web page during a web browsing session, each content signature corresponding with a different portion of the content of the web page, each portion comprising one of text, images, video, and audio; analyze, at the search engine server, the plurality of content signatures to identify a portion of the content that has changed on the web page by determining a difference between at least one of the plurality of content signatures and a content signature accessible by the search engine server; and control crawling of the web page by the search engine server based on the portion of the content that has changed on the web page receive, at the search engine server from an end user's computing device, a content signature of a web page, the content signature comprising a representation of the web page automatically generated from the content of the web page by a client application on the end user's computing device, the web page having been downloaded by the end user's computing device from a content server separate from the search engine server when an end user employed the end user's computing device to access the web page during a web browsing session; compare, at the search engine server, the content signature of the web page received from the end user's computing device to a second content signature of the web page accessible to the search engine server; determine, at the search engine server, a location of content within the web page that has changed based on a difference determined between the content signature of the web page received from the end user's computing device and the second content signature of the web page accessible to the search engine server; and crawl the web page based on determining the location of content within the web page that has changed.
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1. A search engine server comprising: one or more processors; and one or more computer storage media storing computing-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive, at the search engine server from an end user computing device, a plurality of content signatures of a web page, the plurality of content signatures having been automatically generated at the end user computing device from content of the web page downloaded and displayed by the end user computing device, the web page having been downloaded by the end user computing device from one or more content servers separate from the search engine server when an end user employed the end user computing device to access the web page during a web browsing session, each content signature corresponding with a different portion of the content of the web page, each portion comprising one of text, images, video, and audio; analyze, at the search engine server, the plurality of content signatures to identify a portion of the content that has changed on the web page by determining a difference between at least one of the plurality of content signatures and a content signature accessible by the search engine server; and control crawling of the web page by the search engine server based on the portion of the content that has changed on the web page receive, at the search engine server from an end user's computing device, a content signature of a web page, the content signature comprising a representation of the web page automatically generated from the content of the web page by a client application on the end user's computing device, the web page having been downloaded by the end user's computing device from a content server separate from the search engine server when an end user employed the end user's computing device to access the web page during a web browsing session; compare, at the search engine server, the content signature of the web page received from the end user's computing device to a second content signature of the web page accessible to the search engine server; determine, at the search engine server, a location of content within the web page that has changed based on a difference determined between the content signature of the web page received from the end user's computing device and the second content signature of the web page accessible to the search engine server; and crawl the web page based on determining the location of content within the web page that has changed. 5. The search engine server of claim 1 , wherein a first content signature from the plurality of content signatures comprises a hash value generated by the end user computing device applying a hash function to a first portion of the web page.
| 0.532472 |
1. An apparatus for associating and aggregating attributes in a token-based environment, comprising: a memory operable to store a plurality of tokens indicating a device has been identified and is capable of consuming a resource; and a processor operable to: receive a subject token indicating an attempt to authenticate a user that is attempting to access a resource, the subject token representing at least one attribute associated with the user; determine at least one token-based rule based at least in part upon a token in the plurality of tokens and the subject token, the at least one token-based rule indicating a plurality of attributes required to access the resource; determine, from the at least one token-based rule, the plurality of attributes required to access the resource; determine a second plurality of attributes represented by the plurality of tokens and the subject token; determine at least one missing attribute, the at least one missing attribute in the plurality of attributes but not in the second plurality of attributes; request the at least one missing attribute; and receive, in response to the request for the at least one missing attribute, a first token representing the at least one missing attribute.
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1. An apparatus for associating and aggregating attributes in a token-based environment, comprising: a memory operable to store a plurality of tokens indicating a device has been identified and is capable of consuming a resource; and a processor operable to: receive a subject token indicating an attempt to authenticate a user that is attempting to access a resource, the subject token representing at least one attribute associated with the user; determine at least one token-based rule based at least in part upon a token in the plurality of tokens and the subject token, the at least one token-based rule indicating a plurality of attributes required to access the resource; determine, from the at least one token-based rule, the plurality of attributes required to access the resource; determine a second plurality of attributes represented by the plurality of tokens and the subject token; determine at least one missing attribute, the at least one missing attribute in the plurality of attributes but not in the second plurality of attributes; request the at least one missing attribute; and receive, in response to the request for the at least one missing attribute, a first token representing the at least one missing attribute. 4. The apparatus of claim 1 , the processor further operable to: generate a session token representing a session, the session facilitating access by the device to the resource; correlate the plurality of tokens, the subject token, and the first token with the session token.
| 0.579946 |
1. A system for calibrating a document processing device from a composite document, comprising: an input device to receive input of a composite document comprising an image human-readable content located in a foreground of the document and positioned relative to machine-readable code marks located in a background that are registered with the human-readable content and are encoded with at least one spatial pointer comprising a location identifier and supplementary information comprising at least one of human-readable characters, physical parameters, predefined information, and reference values for an ideal version of the human-readable content into a document processing device; a decoding module to decode the machine-readable code marks to determine the location identifier and the supplementary information, wherein the location identifier comprises spatial relationships of the relative positions between the foreground and the background for the ideal version of the human-readable content; a comparison module to compare the spatial relationships of the ideal version of the human-readable content with spatial relationships between the foreground and the background of the composite document and to identify distortions based on the comparison; and a calibration module to calibrate the document processing device based on the identified distortions.
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1. A system for calibrating a document processing device from a composite document, comprising: an input device to receive input of a composite document comprising an image human-readable content located in a foreground of the document and positioned relative to machine-readable code marks located in a background that are registered with the human-readable content and are encoded with at least one spatial pointer comprising a location identifier and supplementary information comprising at least one of human-readable characters, physical parameters, predefined information, and reference values for an ideal version of the human-readable content into a document processing device; a decoding module to decode the machine-readable code marks to determine the location identifier and the supplementary information, wherein the location identifier comprises spatial relationships of the relative positions between the foreground and the background for the ideal version of the human-readable content; a comparison module to compare the spatial relationships of the ideal version of the human-readable content with spatial relationships between the foreground and the background of the composite document and to identify distortions based on the comparison; and a calibration module to calibrate the document processing device based on the identified distortions. 6. A system according to claim 1 , wherein the supplementary information comprises at least one of position, size, shape, color, grey scale, hue, luminance, and radiance.
| 0.779639 |
1. A method of providing a recommendation comprising: measuring a distance by a processor between a first document and each second document in a plurality of other documents by: compressing the first document to determine a first size, compressing a second document to determine a second size, compressing a concatenation of the first document and the second document to determine a third size, and determining a compression-based dissimilarity measurement based on a ratio between the third size and a sum of the first size and the second size, wherein the first document and a second document are more closely related if the compression-based dissimilarity measurement is lower, the first document and a second document are less closely related if the compression-based dissimilarity measure is higher, and the compression based dissimilarity measurement has a value that is not greater than one; organizing a cluster comprising the first document and one or more of the other documents based on the measured distances between the first document and the other documents by the processor; categorizing the cluster based on a common subject matter between the clustered documents by the processor; and selecting one or more documents based on the category of the cluster.
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1. A method of providing a recommendation comprising: measuring a distance by a processor between a first document and each second document in a plurality of other documents by: compressing the first document to determine a first size, compressing a second document to determine a second size, compressing a concatenation of the first document and the second document to determine a third size, and determining a compression-based dissimilarity measurement based on a ratio between the third size and a sum of the first size and the second size, wherein the first document and a second document are more closely related if the compression-based dissimilarity measurement is lower, the first document and a second document are less closely related if the compression-based dissimilarity measure is higher, and the compression based dissimilarity measurement has a value that is not greater than one; organizing a cluster comprising the first document and one or more of the other documents based on the measured distances between the first document and the other documents by the processor; categorizing the cluster based on a common subject matter between the clustered documents by the processor; and selecting one or more documents based on the category of the cluster. 4. The method of claim 1 , wherein the first document and the other documents comprise electronic files containing data representative of questions and answers.
| 0.608426 |
1. A computer implemented method for implementing a mixed-signal electronic design using standardized power data, comprising: at least one processor or at least one processor core executing a process, the process comprising: identifying a mixed-signal electronic design; identifying, generating, or modifying, with an aid of a standardized power format mechanism including or coupled with the at least one processor, standardized power data in a standardized power format having an illegal signal in the mixed-signal electronic design by introducing one or more changes to generate updated standardized power data from the standardized power data; and implementing the mixed-signal electronic design by using the updated standardized power data including the illegal signal for manufacturing of a mixed signal electronic circuit, wherein the illegal signal is not recognized by a standardized power format framework for the standardized power format and comprises at least one of a power control signal or an expression including an incompatible or illegal signal to implement power intent for the mixed-signal electronic design.
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1. A computer implemented method for implementing a mixed-signal electronic design using standardized power data, comprising: at least one processor or at least one processor core executing a process, the process comprising: identifying a mixed-signal electronic design; identifying, generating, or modifying, with an aid of a standardized power format mechanism including or coupled with the at least one processor, standardized power data in a standardized power format having an illegal signal in the mixed-signal electronic design by introducing one or more changes to generate updated standardized power data from the standardized power data; and implementing the mixed-signal electronic design by using the updated standardized power data including the illegal signal for manufacturing of a mixed signal electronic circuit, wherein the illegal signal is not recognized by a standardized power format framework for the standardized power format and comprises at least one of a power control signal or an expression including an incompatible or illegal signal to implement power intent for the mixed-signal electronic design. 3. The computer implemented method of claim 1 , wherein the act of implementing the mixed-signal electronic design using updated standardized power data including the illegal signal is performed without using one or more wrappers for an electronic circuit design block that generates the illegal signal.
| 0.721125 |
11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to select a subset of a set of comments associated with a group of documents, the program module including: instructions for accessing, at memory locations in the memory, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and instructions for selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function.
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11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to select a subset of a set of comments associated with a group of documents, the program module including: instructions for accessing, at memory locations in the memory, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and instructions for selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function. 15. The apparatus of claim 11 , wherein the program module further includes instructions for obtaining annotations for the subset after selecting the subset, by: masking a remainder of the set of comments so that only the subset is presented to reviewers; and receiving the annotations for the subset from the reviewers.
| 0.5 |
12. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device, cause the computing device to perform operations comprising: providing a text object for output at a first location on a proximity-sensitive display; receiving data indicating a touch received at a second location on the proximity-sensitive display; determining a confidence value that reflects an input-to-text engine's confidence that text associated with the text object accurately represents an input; determining whether the touch received through the proximity-sensitive display represents a selection of the text based at least on (i) the confidence value that reflects the input-to-text engine's confidence that the text is an accurate representation of the input, (ii) the first location of the text object on the proximity-sensitive display, and (iii) the second location of the touch on the proximity-sensitive display; and providing an indication of whether the touch received through the proximity-sensitive display represents a selection of the text.
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12. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device, cause the computing device to perform operations comprising: providing a text object for output at a first location on a proximity-sensitive display; receiving data indicating a touch received at a second location on the proximity-sensitive display; determining a confidence value that reflects an input-to-text engine's confidence that text associated with the text object accurately represents an input; determining whether the touch received through the proximity-sensitive display represents a selection of the text based at least on (i) the confidence value that reflects the input-to-text engine's confidence that the text is an accurate representation of the input, (ii) the first location of the text object on the proximity-sensitive display, and (iii) the second location of the touch on the proximity-sensitive display; and providing an indication of whether the touch received through the proximity-sensitive display represents a selection of the text. 15. The storage device of claim 12 , wherein: receiving, by the input-to-text engine, input comprises receiving, by the input-to-text engine, audio data that encodes an utterance; and determining the confidence value that reflects the input-to-text engine's confidence that the generated text accurately represents the received input comprises determining a confidence value that reflects the input-to-text engine's confidence that the generated text accurately represents one or more terms spoken in the utterance.
| 0.728304 |
4. The apparatus according to claim 1 , wherein the attribute-information generator comprises: an attribute-conversion-rule generator configured to generate an attribute conversion function for converting the attribute information of the conversion-target speaker to the attribute information of the conversion-source speaker; an attribute-information extractor configured to extract attribute information corresponding to the target-speaker speech units from the speech of the conversion-target speaker or the linguistic information of the speech of the conversion-target speaker; and an attribute-information converter configured to convert the attribute information corresponding to the target-speaker speech units using the attribute conversion function to use the converted attribute information as target-speaker attribute information corresponding to the target-speaker speech units.
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4. The apparatus according to claim 1 , wherein the attribute-information generator comprises: an attribute-conversion-rule generator configured to generate an attribute conversion function for converting the attribute information of the conversion-target speaker to the attribute information of the conversion-source speaker; an attribute-information extractor configured to extract attribute information corresponding to the target-speaker speech units from the speech of the conversion-target speaker or the linguistic information of the speech of the conversion-target speaker; and an attribute-information converter configured to convert the attribute information corresponding to the target-speaker speech units using the attribute conversion function to use the converted attribute information as target-speaker attribute information corresponding to the target-speaker speech units. 5. The apparatus according to claim 4 , wherein the attribute-conversion-rule generator comprises: a analyzer configured to find an average of the fundamental frequency information of the conversion-target speaker and an average of the fundamental frequency information of the conversion-source speaker; and a difference generator configured to determine difference between the average of the fundamental frequency information of the conversion-target speaker and the average of the fundamental frequency information of the conversion-source speaker, and generates an attribute conversion function in which the difference is added to the fundamental frequency information of the conversion-source speaker.
| 0.713474 |
1. A method comprising: extracting a portion of style information from at least one source of style information, the portion of style information extracted corresponding to content that is identified by a user for copying from a source document, at least some of the style information being demarcated separately from the user-identified content, and the portion of style information being extracted from a source of style information that is external to the source document from which the user-identified content is identified responsive to a determination that the at least one source of style information includes an external source of style information; storing the portion of style information that is extracted with the user-identified content that is extracted in a clipboard store; and responsive to input to paste at least one portion of the stored content at a specified location within a target document, reconstructing the at least one portion of stored content at the specified location using the extracted portion of style information to have a same visual appearance at the specified location as in the source document.
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1. A method comprising: extracting a portion of style information from at least one source of style information, the portion of style information extracted corresponding to content that is identified by a user for copying from a source document, at least some of the style information being demarcated separately from the user-identified content, and the portion of style information being extracted from a source of style information that is external to the source document from which the user-identified content is identified responsive to a determination that the at least one source of style information includes an external source of style information; storing the portion of style information that is extracted with the user-identified content that is extracted in a clipboard store; and responsive to input to paste at least one portion of the stored content at a specified location within a target document, reconstructing the at least one portion of stored content at the specified location using the extracted portion of style information to have a same visual appearance at the specified location as in the source document. 2. The method as recited in claim 1 , wherein the at least one source of style information is external to the source document from which the content is identified.
| 0.661635 |
14. A computer-implemented method comprising: accessing an item database storing item records, each of the item records including an attribute, an attribute value, and a reference to a product record of a plurality of product records; accessing a product database storing the plurality of product records, the product database being representative of a decision tree having end nodes, each of the end nodes corresponding uniquely to one of the plurality of product records; performing an analysis of the product database based on the item records and on the plurality of product records, the analysis including a determination of a compression ratio based on a first total number of item records and on a second total number of product records, the analysis being performed by a hardware-implemented manager module of a machine; modifying the product database based on the analysis, the modifying being performed by the hardware-implemented manager module of the machine.
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14. A computer-implemented method comprising: accessing an item database storing item records, each of the item records including an attribute, an attribute value, and a reference to a product record of a plurality of product records; accessing a product database storing the plurality of product records, the product database being representative of a decision tree having end nodes, each of the end nodes corresponding uniquely to one of the plurality of product records; performing an analysis of the product database based on the item records and on the plurality of product records, the analysis including a determination of a compression ratio based on a first total number of item records and on a second total number of product records, the analysis being performed by a hardware-implemented manager module of a machine; modifying the product database based on the analysis, the modifying being performed by the hardware-implemented manager module of the machine. 16. The computer-implemented method of claim 14 , wherein: the performing of the analysis includes determining an age of one of the plurality of product records.
| 0.629933 |
1. A computer-implemented robust method for fusing data from different information sources using a training set having a plurality of training examples, each training example having a plurality of disjoint views, the method comprising: a) initially assigning weights, by the computer, to each of the plurality of training examples; b) sampling the training examples, by the computer, based on the distribution of the weights of the training examples; c) iteratively, by the computer, for each of the views, separately training weak classifiers in parallel on the sample of training examples; d) selecting, by the computer, the weak classifier corresponding to the view with the lowest training error rate among all the views and calculating a combination weight value associated with the selected classifier as a function of the lowest training error rate at that iteration; e) updating the weights of the sampled training examples by, for each of the sampled training examples, assigning the same updated weight for sampling the training examples for all views, the updated weight distribution being a function of-the lowest training error rate among all views at that iteration; f) repeating said b) sampling, c) training, d) selecting, and e) updating for a predetermined number of iterations; and g) forming a final classifier that is a sum of the selected weak learners weighted by the corresponding combination weight value at each iteration.
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1. A computer-implemented robust method for fusing data from different information sources using a training set having a plurality of training examples, each training example having a plurality of disjoint views, the method comprising: a) initially assigning weights, by the computer, to each of the plurality of training examples; b) sampling the training examples, by the computer, based on the distribution of the weights of the training examples; c) iteratively, by the computer, for each of the views, separately training weak classifiers in parallel on the sample of training examples; d) selecting, by the computer, the weak classifier corresponding to the view with the lowest training error rate among all the views and calculating a combination weight value associated with the selected classifier as a function of the lowest training error rate at that iteration; e) updating the weights of the sampled training examples by, for each of the sampled training examples, assigning the same updated weight for sampling the training examples for all views, the updated weight distribution being a function of-the lowest training error rate among all views at that iteration; f) repeating said b) sampling, c) training, d) selecting, and e) updating for a predetermined number of iterations; and g) forming a final classifier that is a sum of the selected weak learners weighted by the corresponding combination weight value at each iteration. 3. The computer-implemented method of claim 1 , wherein the initially assigned weight for each training example is 1/N, wherein N is a total number of training examples in the training set.
| 0.617528 |
12. A network management system employing at least one hardware processor comprising: a network manager including the at least one hardware processor; a storage device in which the network manager stores a set of design filters; a graphical user interface through which users interact with the network manager; and a network interface through which the network manager obtains information about network devices; the network manager configured to store the set of design filters in the storage device by providing at least one input screen via the graphical user interface; receiving a design filter script via the at least one input screen, wherein the design filter script includes primitives for searching lines and paragraphs in the network device configuration files having specified attributes; converting the design filter script into an executable design filter, the executable design filter configured to implement the searching when executed; and storing at least one of the design filter script or the executable design filter in the storage device; the network manager further configured to receive, via the graphical user interface, user input identifying a selected design filter from among the set of design filters and selecting a plurality of network device configuration files; the network manager further configured to apply the selected design filter to the plurality of selected network device configuration files to produce filtered results, including the filtered results for the plurality of network device configuration files; and the network manager further configured to provide the filtered results via the graphical user interface for display on a user display device, the filtered results provided via a screen having at least two windows arranged side-by-side within the screen, each window including the filtered results associated with one of the plurality of network device configuration files, the filtered results displayed as at least one of individual commands or command lines from the plurality of network device configuration files.
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12. A network management system employing at least one hardware processor comprising: a network manager including the at least one hardware processor; a storage device in which the network manager stores a set of design filters; a graphical user interface through which users interact with the network manager; and a network interface through which the network manager obtains information about network devices; the network manager configured to store the set of design filters in the storage device by providing at least one input screen via the graphical user interface; receiving a design filter script via the at least one input screen, wherein the design filter script includes primitives for searching lines and paragraphs in the network device configuration files having specified attributes; converting the design filter script into an executable design filter, the executable design filter configured to implement the searching when executed; and storing at least one of the design filter script or the executable design filter in the storage device; the network manager further configured to receive, via the graphical user interface, user input identifying a selected design filter from among the set of design filters and selecting a plurality of network device configuration files; the network manager further configured to apply the selected design filter to the plurality of selected network device configuration files to produce filtered results, including the filtered results for the plurality of network device configuration files; and the network manager further configured to provide the filtered results via the graphical user interface for display on a user display device, the filtered results provided via a screen having at least two windows arranged side-by-side within the screen, each window including the filtered results associated with one of the plurality of network device configuration files, the filtered results displayed as at least one of individual commands or command lines from the plurality of network device configuration files. 18. A network management system according to claim 12 , wherein the network manager is configured to apply the selected design filter by applying the executable design filter to the plurality of network device configuration files.
| 0.531562 |
1. A digital music library builder comprising: a receiver to receive broadcast audio from a first broadcast station, and to receive a broadcast image from a second broadcast station; a song extractor, coupled to the receiver, to extract a song from the received broadcast audio, comprising an audio parser to mark the start and end of a song within the received broadcast audio; a meta-data generator, coupled to the receiver, to identify meta-data for the extracted song from the received broadcast image, comprising a luminance extractor to remove color burst noise from the received broadcast image; and a memory, coupled to the song extractor and the meta-data generator, wherein a memory manager automatically stores the extracted song in a digital music library in the memory and automatically associates the identified meta-data with the stored song, within the digital music library.
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1. A digital music library builder comprising: a receiver to receive broadcast audio from a first broadcast station, and to receive a broadcast image from a second broadcast station; a song extractor, coupled to the receiver, to extract a song from the received broadcast audio, comprising an audio parser to mark the start and end of a song within the received broadcast audio; a meta-data generator, coupled to the receiver, to identify meta-data for the extracted song from the received broadcast image, comprising a luminance extractor to remove color burst noise from the received broadcast image; and a memory, coupled to the song extractor and the meta-data generator, wherein a memory manager automatically stores the extracted song in a digital music library in the memory and automatically associates the identified meta-data with the stored song, within the digital music library. 15. The digital music library builder of claim 1 wherein the meta-data generator tracks a number of repetitions of a song that is received repeatedly by the receiver.
| 0.543792 |
10. The non-transitory computer readable medium of claim 9 , wherein the voice profile includes adjustable parameters, wherein the adjustable parameters include one or more of: a pitch of the speech model, a tone of the speech model, a volume of the speech model, and a rhythm of the speech model.
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10. The non-transitory computer readable medium of claim 9 , wherein the voice profile includes adjustable parameters, wherein the adjustable parameters include one or more of: a pitch of the speech model, a tone of the speech model, a volume of the speech model, and a rhythm of the speech model. 11. The non-transitory computer readable medium of claim 10 , wherein the voice profile includes a plurality of voice profiles associated with a speaker of the plurality of spoken utterances, wherein each respective voice profile of the plurality of voice profiles is associated with a respective one or more parameters of the adjustable parameters.
| 0.857878 |
18. The system of claim 15 , wherein the active learning module is further configured to: receive an indication of relevance from the user of at least one term of the second subset; and adjust the model based on the received indication of relevance of at least one term of the second subset.
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18. The system of claim 15 , wherein the active learning module is further configured to: receive an indication of relevance from the user of at least one term of the second subset; and adjust the model based on the received indication of relevance of at least one term of the second subset. 19. The system of claim 18 , wherein the active learning module is further operative to: receive a third plurality of semantically related terms from the keyword suggestion tool; and select a third subset comprising at least one term of the third plurality of semantically related terms based on the adjusted model and one or more properties of the third plurality of semantically related terms.
| 0.873563 |
1. A method of encoding on a computer system for information retrieval an inverted list structure of annotation material, the method comprising: collecting a group of documents and storing the group of documents in a digital format; determining a group of external annotations referencing the group of documents; forming a snippet index by grouping the group of external annotations by unique annotation identifier; forming a snippet dictionary which, for each unique annotation identifier, indexes a corresponding position in the snippet index for the group of external annotations having that unique annotation identifier; computing a similarity score between a user query and document annotations utilizing a similarity function; and utilizing the similarity function to rank the relevant documents, wherein annotation relevance weightings are stored with the annotations in said snippet index, wherein the same annotation may be applied with high frequency to certain documents and wherein multiple annotations for a single document are grouped into a single annotation identifier with aggregated weight.
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1. A method of encoding on a computer system for information retrieval an inverted list structure of annotation material, the method comprising: collecting a group of documents and storing the group of documents in a digital format; determining a group of external annotations referencing the group of documents; forming a snippet index by grouping the group of external annotations by unique annotation identifier; forming a snippet dictionary which, for each unique annotation identifier, indexes a corresponding position in the snippet index for the group of external annotations having that unique annotation identifier; computing a similarity score between a user query and document annotations utilizing a similarity function; and utilizing the similarity function to rank the relevant documents, wherein annotation relevance weightings are stored with the annotations in said snippet index, wherein the same annotation may be applied with high frequency to certain documents and wherein multiple annotations for a single document are grouped into a single annotation identifier with aggregated weight. 5. A method as claimed in claim 1 wherein annotations within the snippet index are stored in decreasing order of frequency of occurrence.
| 0.642263 |
3. The method of claim 1 , said identifying said missing information comprising evaluating a piece of evidence relevant to said candidate answer to identify said missing information.
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3. The method of claim 1 , said identifying said missing information comprising evaluating a piece of evidence relevant to said candidate answer to identify said missing information. 4. The method of claim 3 , said evaluating a piece of evidence comprising: parsing said question into a first collection of elements; parsing said piece of evidence into a second collection of elements; analyzing said first collection of elements for said question and said piece of evidence in order to determine a relationship between a first element of said first collection of elements for said question and a second element of said second collection of elements for said piece of evidence; and locating a missing relationship between said first element and said second element, said missing relationship comprising said missing information.
| 0.882881 |
1. A call router comprising: a memory storing program instructions and a rule set; a telephone interface configured to receive a speech signal representing words spoken by a caller; a processor coupled to the memory and the telephone interface, wherein the processor is configured to perform functions in response to executing the programming instructions stored in the memory, including functions of: in response to the received speech signal, produce recognized text having words representative of the spoken words; detect a class of the words in the recognized text, wherein the class is a group of words having a common attribute and each class of words is assigned a weight; in response to detection of a combination of classes in the recognized text, identify rules that contain matches to the combination of classes detected in the recognized text from among multiple rules defining destinations for different combinations of classes; select a rule from the identified rules based on a number of detected classes and a corresponding sum of the weights assigned to the classes in the combination of classes in the recognized text; interpret the selected rule to identify a destination for routing the call; and route the call to the identified destination.
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1. A call router comprising: a memory storing program instructions and a rule set; a telephone interface configured to receive a speech signal representing words spoken by a caller; a processor coupled to the memory and the telephone interface, wherein the processor is configured to perform functions in response to executing the programming instructions stored in the memory, including functions of: in response to the received speech signal, produce recognized text having words representative of the spoken words; detect a class of the words in the recognized text, wherein the class is a group of words having a common attribute and each class of words is assigned a weight; in response to detection of a combination of classes in the recognized text, identify rules that contain matches to the combination of classes detected in the recognized text from among multiple rules defining destinations for different combinations of classes; select a rule from the identified rules based on a number of detected classes and a corresponding sum of the weights assigned to the classes in the combination of classes in the recognized text; interpret the selected rule to identify a destination for routing the call; and route the call to the identified destination. 9. The call router of claim 1 , wherein the processor is configured to perform additional functions, including functions to recognize the words spoken in natural language.
| 0.603606 |
7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module.
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7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module. 8. The apparatus according to claim 7 , wherein the information process module determines an output reference link for the first document based on the probability value of the input reference link using the Markov chain model, calculates an output reference link using the Markov chain model for a second document, which has the output reference link for the first document as an input reference link, and connects the calculated reference links to provide the information about the main knowledge stream.
| 0.5 |
1. A network apparatus, comprising: a document parser to parse a document having transaction information and to create a document object from said transaction information; a pattern parser to parse pattern information of a pattern for one or more elements according to a predefined pattern object data structure and to place said elements in appropriate blocks within said pattern object data structure; a pattern object generator to receive said pattern information of a pattern and to create a pattern object from said pattern information; and content based switching decision logic to make a switching decision for a message based upon a comparison of said document object with said pattern object, said pattern object contains at least one expression, and said content based switching logic evaluates said at least one expression for a match with said document object.
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1. A network apparatus, comprising: a document parser to parse a document having transaction information and to create a document object from said transaction information; a pattern parser to parse pattern information of a pattern for one or more elements according to a predefined pattern object data structure and to place said elements in appropriate blocks within said pattern object data structure; a pattern object generator to receive said pattern information of a pattern and to create a pattern object from said pattern information; and content based switching decision logic to make a switching decision for a message based upon a comparison of said document object with said pattern object, said pattern object contains at least one expression, and said content based switching logic evaluates said at least one expression for a match with said document object. 2. The network apparatus of claim 1 , further comprising a document object generator to receive said document having transaction information.
| 0.771478 |
1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects.
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1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects. 2. The method of claim 1 , wherein the processing the plurality of manual test cases comprises presenting a guideline for generating the plurality of manual test cases.
| 0.503344 |
1. A computer-based language immersion teaching system comprising: (a) a digital processing device comprising a memory and an operating system configured to perform executable instructions; and (b) a computer program, provided to the digital processing device, including executable instructions that create a language immersion teaching environment, wherein the environment comprises a plurality of learning activities associated with a target language; wherein the language immersion teaching environment and the plurality of learning activities are suitable for a learner aged about 3 to about 10 years; wherein the plurality of activities comprises: i. at least one learning activity based on a taxonomy of phonemes; ii. at least one learning activity selected from: songs, chants, books, poems, puzzles, games, art activities, and printable activities; iii. voiceover audio in the target language; and iv. a software module for recording the learner's pronunciation and comparing it to one or more model pronunciations.
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1. A computer-based language immersion teaching system comprising: (a) a digital processing device comprising a memory and an operating system configured to perform executable instructions; and (b) a computer program, provided to the digital processing device, including executable instructions that create a language immersion teaching environment, wherein the environment comprises a plurality of learning activities associated with a target language; wherein the language immersion teaching environment and the plurality of learning activities are suitable for a learner aged about 3 to about 10 years; wherein the plurality of activities comprises: i. at least one learning activity based on a taxonomy of phonemes; ii. at least one learning activity selected from: songs, chants, books, poems, puzzles, games, art activities, and printable activities; iii. voiceover audio in the target language; and iv. a software module for recording the learner's pronunciation and comparing it to one or more model pronunciations. 7. The computer-based system of claim 1 , wherein the taxonomy of phonemes includes phonemes represented by an image.
| 0.600503 |
1. A computer-implemented method for tracking one or more catheter objects in a sequence of images, the method comprising: determining, by a computer, a foreground portion of the first image comprising portions of the first image corresponding to one or more catheter electrode locations; determining, by the computer, a background portion of the first image which excludes the foreground portion; applying, by the computer, a steerable filter or a pre-processing method to the background portion of the first image to create a non-catheter structures mask which excludes ridge-like structures in the background portion of the first image; generating, by the computer, a dictionary based on catheter object locations in the first image, wherein sparse coding is used to represent the non-catheter structures mask as a plurality of basis vectors in the dictionary; identifying, by the computer, one or more catheter object landmark candidates in the sequence of images; generating, by the computer, a plurality of tracking hypothesis for the catheter object landmark candidates; generating, by the computer, a voting score for the catheter object landmark candidates based on a voting contribution of each of a plurality of image patches used to localize the catheter object locations in the first image; and selecting, by the computer, a first tracking hypothesis from the plurality of tracking hypothesis based on the dictionary and the voting score.
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1. A computer-implemented method for tracking one or more catheter objects in a sequence of images, the method comprising: determining, by a computer, a foreground portion of the first image comprising portions of the first image corresponding to one or more catheter electrode locations; determining, by the computer, a background portion of the first image which excludes the foreground portion; applying, by the computer, a steerable filter or a pre-processing method to the background portion of the first image to create a non-catheter structures mask which excludes ridge-like structures in the background portion of the first image; generating, by the computer, a dictionary based on catheter object locations in the first image, wherein sparse coding is used to represent the non-catheter structures mask as a plurality of basis vectors in the dictionary; identifying, by the computer, one or more catheter object landmark candidates in the sequence of images; generating, by the computer, a plurality of tracking hypothesis for the catheter object landmark candidates; generating, by the computer, a voting score for the catheter object landmark candidates based on a voting contribution of each of a plurality of image patches used to localize the catheter object locations in the first image; and selecting, by the computer, a first tracking hypothesis from the plurality of tracking hypothesis based on the dictionary and the voting score. 10. The method of claim 1 , wherein the sequence of images comprises a plurality of fluoroscopic images.
| 0.666174 |
1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy.
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1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. 7. The portable dataport of claim 1 , wherein the portable dataport allows the user to toggle back and forth from the currently viewed document to a previously viewed document, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to the previously viewed document when the previously viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the previously viewed document is the same as the viewable area of the currently viewed document.
| 0.637084 |
12. A computing system that processes queries on graph data, comprising: a memory; a security policy logic that stores data access constraints as match pattern and apply pattern pairs in the memory, where each match pattern specifies a selection criteria that identifies the resources that are subject to a security policy, and where associated apply pattern specifies one or more security conditions, in the form of graph patterns to be included with any query that satisfies the match pattern criteria; an access control enforcement logic that expresses query selection criteria in a tree representation of an abstract syntactic structure using metadata, analyzes the tree representation to collect properties and any terms or variables in subject or object positions with respect to the collected properties; determines a match pattern corresponding to at least one of the collected properties, terms, or variables in the query selection criteria; and rewrites the query to include, as security conditions, the graph patterns from the apply pattern that is paired with the determined match pattern; and a query processor for executing the rewritten query on graph data such that data instances returned by the rewritten query satisfy the data access constraints specified by the match pattern and apply pattern.
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12. A computing system that processes queries on graph data, comprising: a memory; a security policy logic that stores data access constraints as match pattern and apply pattern pairs in the memory, where each match pattern specifies a selection criteria that identifies the resources that are subject to a security policy, and where associated apply pattern specifies one or more security conditions, in the form of graph patterns to be included with any query that satisfies the match pattern criteria; an access control enforcement logic that expresses query selection criteria in a tree representation of an abstract syntactic structure using metadata, analyzes the tree representation to collect properties and any terms or variables in subject or object positions with respect to the collected properties; determines a match pattern corresponding to at least one of the collected properties, terms, or variables in the query selection criteria; and rewrites the query to include, as security conditions, the graph patterns from the apply pattern that is paired with the determined match pattern; and a query processor for executing the rewritten query on graph data such that data instances returned by the rewritten query satisfy the data access constraints specified by the match pattern and apply pattern. 14. The computing system of claim 12 comprising a context generation logic that retrieves context information regarding a query processing session and further where the access control enforcement logic inserts context information in the apply pattern when rewriting the query.
| 0.5 |
21. A computing apparatus, comprising: a display unit that is capable of generating video images; an input device; a processing apparatus operatively coupled to said display unit and said input device, said processing apparatus comprising a processor and a memory operatively coupled to said processor, a network interface connected to a network and to the processing apparatus; said processing apparatus being programmed to select a template in an accounting program wherein the template has a field related to the selected template; said processing apparatus being programmed to identify an open field in the selected template that can be filled in with data from the accounting program; said processing apparatus being programmed to select data stored by the accounting program that is appropriate to fill in the open field in the selected template; said processing apparatus being programmed to communicate the selected data and the selected template to the word processing program; said processing apparatus being programmed to open a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and said processing apparatus being programmed to allow the modifications made on the word processing document to be communicated to the accounting program.
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21. A computing apparatus, comprising: a display unit that is capable of generating video images; an input device; a processing apparatus operatively coupled to said display unit and said input device, said processing apparatus comprising a processor and a memory operatively coupled to said processor, a network interface connected to a network and to the processing apparatus; said processing apparatus being programmed to select a template in an accounting program wherein the template has a field related to the selected template; said processing apparatus being programmed to identify an open field in the selected template that can be filled in with data from the accounting program; said processing apparatus being programmed to select data stored by the accounting program that is appropriate to fill in the open field in the selected template; said processing apparatus being programmed to communicate the selected data and the selected template to the word processing program; said processing apparatus being programmed to open a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and said processing apparatus being programmed to allow the modifications made on the word processing document to be communicated to the accounting program. 30. The computing apparatus of claim 21 , the processing apparatus being programmed to print using the word processing program in such that the word processing program operates internally and is not visible to the user.
| 0.5266 |
5. The system of claim 1 , further comprising: a Tolerator module that alters the search request by including related terms.
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5. The system of claim 1 , further comprising: a Tolerator module that alters the search request by including related terms. 6. The system of claim 5 , wherein the related terms are one of a computer, laptop computer, personal computer, personal data assistant, a camera, a phone, a cell phone, mobile phone, a computer server, a media server, a music player, a game box, a smart phone, a data storage device, measuring device, handheld scanner, a scanning device, a barcode reader, a POS device, digital assistant, desk phone, IP phone, solid-state memory device, and a memory card.
| 0.798507 |
1. A tool for annotating an event map, comprising: a map generator for generating an event map depicting a schedule of activities for an event including plural sessions; an annotating unit for annotating said event map based on a user input, the annotating of the event map comprising tagging information to a feature of the event map; a view generator for generating a zoomable and pannable view of the schedule of activities depicted by said annotated event map; and a display device for displaying said zoomable and pannable view of the schedule of activities depicted by said annotated event map.
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1. A tool for annotating an event map, comprising: a map generator for generating an event map depicting a schedule of activities for an event including plural sessions; an annotating unit for annotating said event map based on a user input, the annotating of the event map comprising tagging information to a feature of the event map; a view generator for generating a zoomable and pannable view of the schedule of activities depicted by said annotated event map; and a display device for displaying said zoomable and pannable view of the schedule of activities depicted by said annotated event map. 12. The tool of claim 1 , further comprising: a storage device for storing said annotated event map.
| 0.751858 |
6. A method in a computing system for processing a search request against a dimensional model of a set of documents, the model comprising a fact table and two or more dimension table, the fact table being comprised of rows each containing a document reference and referencing, for each attribute for which an attribute value was extracted, a row corresponding to the attribute value in a dimension table of the dimensional model corresponding to the attribute, the method comprising: receiving a search request specifying search request attribute tests for one or more of the set of attributes; for each of the set of attributes for which a search request attribute test is specified, selecting the rows of the dimension table corresponding to the attribute that satisfy the search request attribute test; joining the selected rows of the dimension tables corresponding to the attributes for which a search request attribute value is specified to the fact table to produce a join result; and generating a search request result containing the document references contained by the rows of the join result.
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6. A method in a computing system for processing a search request against a dimensional model of a set of documents, the model comprising a fact table and two or more dimension table, the fact table being comprised of rows each containing a document reference and referencing, for each attribute for which an attribute value was extracted, a row corresponding to the attribute value in a dimension table of the dimensional model corresponding to the attribute, the method comprising: receiving a search request specifying search request attribute tests for one or more of the set of attributes; for each of the set of attributes for which a search request attribute test is specified, selecting the rows of the dimension table corresponding to the attribute that satisfy the search request attribute test; joining the selected rows of the dimension tables corresponding to the attributes for which a search request attribute value is specified to the fact table to produce a join result; and generating a search request result containing the document references contained by the rows of the join result. 8. The method of claim 6 , wherein one of the specified search request attribute tests tests whether the attribute to which it corresponds is non-null.
| 0.721316 |
1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server configured to create a new social network automatically, the server enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the new social network, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; the server automatically, without need of user consent, without any upfront registration requirements or invitations, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in the new social network based on the GPS coordinates from the corresponding one of the plurality of mobile devices; and the social networking website system facilitating creation and sharing of new postings, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein a current location to social networks mapping is used to determine appropriate social networks and associated social groups, in the street, city, county, region, state or country in which the user can participate in; wherein the social networking website system also provides each user the ability to create their own social groups to share postings on common interests or affiliations.
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1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server configured to create a new social network automatically, the server enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the new social network, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; the server automatically, without need of user consent, without any upfront registration requirements or invitations, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in the new social network based on the GPS coordinates from the corresponding one of the plurality of mobile devices; and the social networking website system facilitating creation and sharing of new postings, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein a current location to social networks mapping is used to determine appropriate social networks and associated social groups, in the street, city, county, region, state or country in which the user can participate in; wherein the social networking website system also provides each user the ability to create their own social groups to share postings on common interests or affiliations. 7. The social networking website system of claim 1 wherein the new message comprises an audio message and a digital photo.
| 0.62386 |
1. An image forming apparatus comprising: a scan apparatus to scan a document received by the image forming apparatus; a text/image separation apparatus to separate the scanned document into a text area and an image area, and to separate texts in the text area into symbols based on pixel data of the separated text area, where the text/image separation unit compares at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; an index determination apparatus to extract one or more properties of the separated symbols and to compare the extracted symbol properties with one or more index thresholds that are set as an average value of preset symbol properties calculated based on a variation of the preset symbol properties, thereby determining whether text including the symbols is an index object; and an index page creation apparatus to create an index page including the text determined as the index object and information about a page including the text, wherein the index determination apparatus determines the symbols as index-object symbols, groups the index-object symbols, and determines the texts comprising the groups of the index-object symbols as objects in the index, when the extracted symbol properties are greater than the index thresholds.
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1. An image forming apparatus comprising: a scan apparatus to scan a document received by the image forming apparatus; a text/image separation apparatus to separate the scanned document into a text area and an image area, and to separate texts in the text area into symbols based on pixel data of the separated text area, where the text/image separation unit compares at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; an index determination apparatus to extract one or more properties of the separated symbols and to compare the extracted symbol properties with one or more index thresholds that are set as an average value of preset symbol properties calculated based on a variation of the preset symbol properties, thereby determining whether text including the symbols is an index object; and an index page creation apparatus to create an index page including the text determined as the index object and information about a page including the text, wherein the index determination apparatus determines the symbols as index-object symbols, groups the index-object symbols, and determines the texts comprising the groups of the index-object symbols as objects in the index, when the extracted symbol properties are greater than the index thresholds. 3. The image forming apparatus of claim 1 , wherein the index thresholds are a reference value to determine an index-object symbol, the index thresholds comprising one or more of a symbol width threshold, a symbol height threshold, and a stroke width threshold, or the index thresholds are set by a user.
| 0.556838 |
55. A method for electronically managing text-based data, the method comprising: dividing said text-based data into a plurality of portions of text-based data; amending at least one of said plurality of portions of text-based data; storing at least one of said plurality of portions of text-based data; storing said amended portion of text-based data; providing a plurality of attributes, wherein at least one of said plurality of attributes defines at least in part a manner in which at least one of said plurality of portions of text-based data and said amended portion of text-based data can is organizable and linkable in a multidimensional space; associating at least one of said plurality of portions of text-based data and said amended portion of text-based data with at least one link comprising at least one of code or markup language enabled at least in part by at least one of said plurality of attributes; enabling a user to search at least one of said plurality of portions of text-based data and said amended portion of text-based data using at least one of said plurality of attributes; and allowing the results of said search be available to a user by: providing at least one of said plurality of portions of text-based data or said amended portion of text-based data in response to said search; and providing one or both of (I) text, or (ii) one or more selectable links representing at least one additional attribute.
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55. A method for electronically managing text-based data, the method comprising: dividing said text-based data into a plurality of portions of text-based data; amending at least one of said plurality of portions of text-based data; storing at least one of said plurality of portions of text-based data; storing said amended portion of text-based data; providing a plurality of attributes, wherein at least one of said plurality of attributes defines at least in part a manner in which at least one of said plurality of portions of text-based data and said amended portion of text-based data can is organizable and linkable in a multidimensional space; associating at least one of said plurality of portions of text-based data and said amended portion of text-based data with at least one link comprising at least one of code or markup language enabled at least in part by at least one of said plurality of attributes; enabling a user to search at least one of said plurality of portions of text-based data and said amended portion of text-based data using at least one of said plurality of attributes; and allowing the results of said search be available to a user by: providing at least one of said plurality of portions of text-based data or said amended portion of text-based data in response to said search; and providing one or both of (I) text, or (ii) one or more selectable links representing at least one additional attribute. 62. The method according to claim 55 , wherein at least one of said plurality of portions of text-based data and said amendment portion of text-based data comprises legislation or material related to a provision of said legislation.
| 0.592909 |
10. The method of claim 9, wherein the partial sentence hypothesis error calculation comprises the steps of: (g) associating a word error with each hypothesized word; (h) associating a gap error with each hypothesized word which begins after the end of the last word in the partial sentence hypothesis identified in step (b); (i) associating an overlap error with each hypothesized word which begins before the end of the last word in the partial sentence hypothesis identified in step (b); (j) summing the errors associated with each hypothesized word in steps (f), (g) and (h) together with the partial sentence error of the partial sentence hypothesis identified in step (b) to give a new partial sentence hypothesis error; and (k) associating the new partial sentence hypothesis error with the new partial sentence hypothesis created in step (c).
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10. The method of claim 9, wherein the partial sentence hypothesis error calculation comprises the steps of: (g) associating a word error with each hypothesized word; (h) associating a gap error with each hypothesized word which begins after the end of the last word in the partial sentence hypothesis identified in step (b); (i) associating an overlap error with each hypothesized word which begins before the end of the last word in the partial sentence hypothesis identified in step (b); (j) summing the errors associated with each hypothesized word in steps (f), (g) and (h) together with the partial sentence error of the partial sentence hypothesis identified in step (b) to give a new partial sentence hypothesis error; and (k) associating the new partial sentence hypothesis error with the new partial sentence hypothesis created in step (c). 11. The method of claim 10, wherein the gap error of step (h) is zero whenever silence is associated with the gap between consecutive hypothesized words.
| 0.832321 |
3. The method of claim 1 , wherein said agent terminal uses local processing resources to perform at least one interactive voice response function.
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3. The method of claim 1 , wherein said agent terminal uses local processing resources to perform at least one interactive voice response function. 5. The method of claim 3 , wherein said at least one interactive voice response function includes an automatic speech recognition function.
| 0.909091 |
14. The method of claim 10 , wherein the plurality of components are selected from the group comprising: a data component, a message component, a workflow component, and a presentation component.
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14. The method of claim 10 , wherein the plurality of components are selected from the group comprising: a data component, a message component, a workflow component, and a presentation component. 15. The method of claim 14 , wherein the additional metadata descriptors are configurable to be operatively coupled to the plurality of components through the metadata descriptors of the plurality of components.
| 0.948828 |
7. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: extracting performance data of a process from a data object of an application to an in-memory database of a computer system, wherein the performance data is extracted to the in-memory database in real time from unmodified source data without preaggregation; storing the performance data in the in-memory database; performing statistical analysis on the performance data to generate a model of at least one operational leading indicator (OLI) of the process, the model comprising calculation of a ratio without an index artifact, the ratio evaluating a first condition comprising a lock indicator of the data object in the application, and a second condition evaluating a threshold absolute balance of the data object over a defined number of posting periods, wherein the statistical analysis is performed using in-memory computing directly on the performance data stored in the in-memory database without requiring separate computer hardware; storing the model of the OLI in the in-memory database; causing an in-memory database engine in communication with the model to receive inputs for performance values and performance measures of the process; causing the in-memory database engine to process an output of the statistical analysis of the model in order to produce a cost measure; performing, by the computer system, ongoing measurements of operational performance of the process from the output of the statistical analysis of the model; determining, by the computer system, variations in the operational performance of the process in response to the ongoing measurements; and implementing, by the computer system, corrective action based on the variations in the operational performance of the process.
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7. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: extracting performance data of a process from a data object of an application to an in-memory database of a computer system, wherein the performance data is extracted to the in-memory database in real time from unmodified source data without preaggregation; storing the performance data in the in-memory database; performing statistical analysis on the performance data to generate a model of at least one operational leading indicator (OLI) of the process, the model comprising calculation of a ratio without an index artifact, the ratio evaluating a first condition comprising a lock indicator of the data object in the application, and a second condition evaluating a threshold absolute balance of the data object over a defined number of posting periods, wherein the statistical analysis is performed using in-memory computing directly on the performance data stored in the in-memory database without requiring separate computer hardware; storing the model of the OLI in the in-memory database; causing an in-memory database engine in communication with the model to receive inputs for performance values and performance measures of the process; causing the in-memory database engine to process an output of the statistical analysis of the model in order to produce a cost measure; performing, by the computer system, ongoing measurements of operational performance of the process from the output of the statistical analysis of the model; determining, by the computer system, variations in the operational performance of the process in response to the ongoing measurements; and implementing, by the computer system, corrective action based on the variations in the operational performance of the process. 12. A non-transitory computer readable storage medium as in claim 7 wherein the statistical analysis comprises linear regression.
| 0.52991 |
9. A computer system for allocating a call from a user to an agent, the system comprising: a processor operatively coupled to a memory device, wherein the processor is configured to execute instructions stored in the memory device to perform operations comprising: determining a set of sentiment indicators associated with the user from one or more acoustic parameters of the call; selecting a candidate agent to handle the call based on the set of sentiment indicators and a sentiment handling capability associated with the candidate agent; and allocating the call to the candidate agent.
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9. A computer system for allocating a call from a user to an agent, the system comprising: a processor operatively coupled to a memory device, wherein the processor is configured to execute instructions stored in the memory device to perform operations comprising: determining a set of sentiment indicators associated with the user from one or more acoustic parameters of the call; selecting a candidate agent to handle the call based on the set of sentiment indicators and a sentiment handling capability associated with the candidate agent; and allocating the call to the candidate agent. 11. The system of claim 9 , wherein determining the set of sentiment indicators comprises: measuring an acoustic parameter from a voice of the user; determining a score associated with each sentiment indicator based on the measured acoustic parameter.
| 0.545652 |
1. A server including a processor, the server comprising: a communication application being executed on a Java virtual machine on said server; a unified application framework for call control and media control for building application components of the communication application a call control API for providing a standardized Java interface for call control, said call control API defining a set of class object primitives for call control; a media control API for providing a standardized Java interface for media server control, said media control API defining a set of class object primitives for media control; a unified call control and media control API defining a set of unified class objects constructed from the class object primitives of the call control API and the media control API; and wherein the application components are built from the unified class objects including: a Call object for connecting a leg of communication between an endpoint and the communication application; a Participant object representing an abstract party involved in a conversation; a Join object for effecting an asynchronous join operation on the Participant object; a MediaService object for media control available to a call; an Eventsource object for representing an event source that serializes events from call control and events from media control such that the application component listening said event source only has to deal with one event at a time; and an Observer object for a listener that listen to events from the event source.
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1. A server including a processor, the server comprising: a communication application being executed on a Java virtual machine on said server; a unified application framework for call control and media control for building application components of the communication application a call control API for providing a standardized Java interface for call control, said call control API defining a set of class object primitives for call control; a media control API for providing a standardized Java interface for media server control, said media control API defining a set of class object primitives for media control; a unified call control and media control API defining a set of unified class objects constructed from the class object primitives of the call control API and the media control API; and wherein the application components are built from the unified class objects including: a Call object for connecting a leg of communication between an endpoint and the communication application; a Participant object representing an abstract party involved in a conversation; a Join object for effecting an asynchronous join operation on the Participant object; a MediaService object for media control available to a call; an Eventsource object for representing an event source that serializes events from call control and events from media control such that the application component listening said event source only has to deal with one event at a time; and an Observer object for a listener that listen to events from the event source. 6. The server as in claim 1 , wherein said unified class objects include the Observer object as a unified event handler that ignores events inappropriate to a context of the specific object model.
| 0.542005 |
5. A memory management unit as recited in claim 1, wherein said translator comprises: means for dividing said virtual address signal into a virtual page number signal and a page offset signal; translation means for receiving said page number signal and, if said virtual page number signal can be translated into a physical page number and a domain number and a permission, issuing a physical page number signal and said domain number signal and a permission signal, but if said virtual page number signal cannot be translated into said physical page number and said domain number and said permission, then issuing a translation fault signal, said translation fault signal forming a first part of said first fault indication; permission control logic for receiving said permission signal and said access type signal, determining if an access type corresponding to said access type signal is allowed by said permission signal, and issuing a permission fault signal if said access type signal is not allowed, said permission fault signal forming a second part of said first fault indication; and means for combining said physical page number signal and said page offset signal to produce said physical address signal.
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5. A memory management unit as recited in claim 1, wherein said translator comprises: means for dividing said virtual address signal into a virtual page number signal and a page offset signal; translation means for receiving said page number signal and, if said virtual page number signal can be translated into a physical page number and a domain number and a permission, issuing a physical page number signal and said domain number signal and a permission signal, but if said virtual page number signal cannot be translated into said physical page number and said domain number and said permission, then issuing a translation fault signal, said translation fault signal forming a first part of said first fault indication; permission control logic for receiving said permission signal and said access type signal, determining if an access type corresponding to said access type signal is allowed by said permission signal, and issuing a permission fault signal if said access type signal is not allowed, said permission fault signal forming a second part of said first fault indication; and means for combining said physical page number signal and said page offset signal to produce said physical address signal. 6. A memory management unit as recited in claim 5, wherein said translation means includes: a translation look-aside buffer for receiving said virtual page number signal, comparing said virtual page number signal to a page number table of said translation look-aside buffer and if said virtual page number signal corresponds to a page number entry in said page number table, then issuing said physical page number signal and said domain number signal and said permission signal, but if said virtual page number component does not correspond to a page number entry in said page number table, then issuing a no-match signal; and translation table look-up logic for receiving said no-match signal and said virtual page number signal and transmitting a page number entry to said translation look-aside buffer if an entry stored in said memory corresponds to said virtual page number signal, but issuing said translation fault signal if no entry stored in said memory corresponds to said virtual page number signal.
| 0.715841 |
6. A method comprising: receiving a spoken utterance of a plurality of uttered characters; determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; selecting a plurality of known character sequences that potentially correspond to the identified character sequence; and for each selected known character sequence, scoring such known character sequence, using a processor, based at least in part on a weighting of individual characters that comprise the known character sequence, wherein scoring the known character sequence comprises: for each individual character of the known character sequence, weighting the individual character based on a unigram frequency with which the individual character is known to be uttered, wherein said weighting comprises: determining whether a selected character of the known character sequence matches a selected character of the identified character sequence; and when the selected character of the known character sequence matches the selected character of the identified character sequence: selecting a value that corresponds to the selected character of the known character sequence; and adding the selected value to a cumulative score associated with the known character sequence; and when the selected character of the known character sequence does not match the selected character of the identified character sequence: making no changes to the cumulative score associated with the known character sequence based upon the selected character of the known character sequence.
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6. A method comprising: receiving a spoken utterance of a plurality of uttered characters; determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; selecting a plurality of known character sequences that potentially correspond to the identified character sequence; and for each selected known character sequence, scoring such known character sequence, using a processor, based at least in part on a weighting of individual characters that comprise the known character sequence, wherein scoring the known character sequence comprises: for each individual character of the known character sequence, weighting the individual character based on a unigram frequency with which the individual character is known to be uttered, wherein said weighting comprises: determining whether a selected character of the known character sequence matches a selected character of the identified character sequence; and when the selected character of the known character sequence matches the selected character of the identified character sequence: selecting a value that corresponds to the selected character of the known character sequence; and adding the selected value to a cumulative score associated with the known character sequence; and when the selected character of the known character sequence does not match the selected character of the identified character sequence: making no changes to the cumulative score associated with the known character sequence based upon the selected character of the known character sequence. 7. The method of claim 6 , wherein the selected value is pre-assigned to the character in a character set.
| 0.546682 |
14. A language reordering system for use in statistical machine translation (SMT), said language reordering system comprising: a computer; a training database for storing training data comprising sentences in a first natural language paired with sentences in a second natural language; an alignment model implemented by the computer and configured to match words and phrases in said first natural language to words and phrases in said second natural language, said alignment model utilizing said training data to generate training samples identifying syntactic differences between said first natural language and said second natural language; and a preprocessing module implemented by the computer and coupled with said training database and said alignment model, said preprocessing module configured to generate a body of reordering knowledge based on a syntax of said first natural language and on a plurality of alignment matrices that map first sample sentences in the first natural language with second sample sentences in the second natural language.
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14. A language reordering system for use in statistical machine translation (SMT), said language reordering system comprising: a computer; a training database for storing training data comprising sentences in a first natural language paired with sentences in a second natural language; an alignment model implemented by the computer and configured to match words and phrases in said first natural language to words and phrases in said second natural language, said alignment model utilizing said training data to generate training samples identifying syntactic differences between said first natural language and said second natural language; and a preprocessing module implemented by the computer and coupled with said training database and said alignment model, said preprocessing module configured to generate a body of reordering knowledge based on a syntax of said first natural language and on a plurality of alignment matrices that map first sample sentences in the first natural language with second sample sentences in the second natural language. 15. The language reordering system of claim 14 wherein said preprocessing module is further configured to receive a word string in said first natural language and utilize said reordering knowledge to reorder words from said word string into reordered word strings.
| 0.678123 |
1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; recognizing, by the computing device via the speech recognizer, speech uttered by the user in the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of potential responses based on the recognized speech and the speaker-specific information for the user; ranking, by the computing device, the set of potential responses based on one or more criteria and the speaker-specific information; determining, by the computing device for each response in the set of potential responses, whether the response should be output or should not be output based on the response's ranking; and if the response should be output: selecting, by the computing device from among a plurality of preconfigured output methods, an output method for outputting the response to the user, the selecting being based on the response's ranking; and outputting, by the computing device, the response to the user using the selected output method.
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1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; recognizing, by the computing device via the speech recognizer, speech uttered by the user in the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of potential responses based on the recognized speech and the speaker-specific information for the user; ranking, by the computing device, the set of potential responses based on one or more criteria and the speaker-specific information; determining, by the computing device for each response in the set of potential responses, whether the response should be output or should not be output based on the response's ranking; and if the response should be output: selecting, by the computing device from among a plurality of preconfigured output methods, an output method for outputting the response to the user, the selecting being based on the response's ranking; and outputting, by the computing device, the response to the user using the selected output method. 4. The method of claim 1 wherein the speech recognizer operates in an always on mode, and wherein the speech recognizer identifies the user upon receiving a trigger phrase.
| 0.582677 |
6. The method of claim 2 , wherein each term further comprises a plurality of Boolean expressions, wherein each of the Boolean expressions comprising the first term and the second term include a first Boolean operator, wherein the first term and the second term are combined using a second Boolean operator, and wherein the first and second Boolean operators are different.
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6. The method of claim 2 , wherein each term further comprises a plurality of Boolean expressions, wherein each of the Boolean expressions comprising the first term and the second term include a first Boolean operator, wherein the first term and the second term are combined using a second Boolean operator, and wherein the first and second Boolean operators are different. 7. The method of claim 6 , wherein the first Boolean operator is a logical-and operator, and wherein the second Boolean operator is a logical-or operator.
| 0.971818 |
1. A healthcare dictionary system providing a term repository accessible for use in supporting the operation of a healthcare enterprise, comprising: an input processor for acquiring healthcare transaction message data including data for communication from a first healthcare facility to at least a second different healthcare facility in at least one of a plurality of different communication protocol data formats and being communicated between different facilities of a healthcare enterprise; a data processor for, parsing said acquired transaction message data to identify a communication protocol data format of said transaction message and extracting a term from said acquired transaction message data, comparing said extracted term to terms in a first term repository, said first term repository including at least one of, (a) definitions indicating meaning of a plurality of healthcare terms used by a particular healthcare facility and (b) synonyms of a plurality of healthcare terms used by a particular healthcare facility and updating said first term repository to include said extracted term in response to a determination, said extracted term is absent from said first term repository; and a communication processor for intermittently processing content of said first term repository to be suitable for communication to a second term repository including definitions of a plurality of healthcare terms used by a different healthcare facility.
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1. A healthcare dictionary system providing a term repository accessible for use in supporting the operation of a healthcare enterprise, comprising: an input processor for acquiring healthcare transaction message data including data for communication from a first healthcare facility to at least a second different healthcare facility in at least one of a plurality of different communication protocol data formats and being communicated between different facilities of a healthcare enterprise; a data processor for, parsing said acquired transaction message data to identify a communication protocol data format of said transaction message and extracting a term from said acquired transaction message data, comparing said extracted term to terms in a first term repository, said first term repository including at least one of, (a) definitions indicating meaning of a plurality of healthcare terms used by a particular healthcare facility and (b) synonyms of a plurality of healthcare terms used by a particular healthcare facility and updating said first term repository to include said extracted term in response to a determination, said extracted term is absent from said first term repository; and a communication processor for intermittently processing content of said first term repository to be suitable for communication to a second term repository including definitions of a plurality of healthcare terms used by a different healthcare facility. 9. A system according to claim 1 , wherein said first term repository is used to update a plurality of different health care information system term repositories including said second term repository.
| 0.595302 |
1. A method for component discovery from source code, the method performed by a processor and comprising: receiving source code; determining business classes by excluding packages and classes in the source code; extracting features from the business classes; estimating similarity for business class pairs based on the extracted features by determining textual similarity by using a co-occurrence matrix that is defined as a sequence of the business classes in the source code and a sequence of unique intermediate representation (IR) tokens occurring across the business classes, and evaluating, for the co-occurrence matrix, a frequency of occurrence of an IR token from the IR tokens occurring in a particular business class of the business classes; clustering the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determining interfaces for the components based on the clustering.
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1. A method for component discovery from source code, the method performed by a processor and comprising: receiving source code; determining business classes by excluding packages and classes in the source code; extracting features from the business classes; estimating similarity for business class pairs based on the extracted features by determining textual similarity by using a co-occurrence matrix that is defined as a sequence of the business classes in the source code and a sequence of unique intermediate representation (IR) tokens occurring across the business classes, and evaluating, for the co-occurrence matrix, a frequency of occurrence of an IR token from the IR tokens occurring in a particular business class of the business classes; clustering the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determining interfaces for the components based on the clustering. 6. The method of claim 1 , wherein clustering the business classes based on the similarity further comprises: generating a set of seed clusters by using top weighted edges between business class pairs, wherein the edges represent the similarity for the business class pairs.
| 0.814939 |
21. A computer readable medium having computer-executable instructions that, when executed on one or more processors, performs the following: construct a first table user interface (UI) for display within a document including text and table, wherein the table supports full spreadsheet functionality; create a first cell table to hold data for the first table UI; construct a second table user interface (UI) for display within the document; create a second cell table to hold a formula for the second table UI, the formula referencing the data in the first cell table; upon modification of the data in the first cell table, automatically recalculate the formula in the second cell table to produce a new result; and providing a document behavior operation including one or more of spell checking, grammar checking, find, replace, and text formatting, across table boundaries, such that when invoked, document behavior operations that are applied to the text outside of the table are applied across a table boundary to text inside the table.
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21. A computer readable medium having computer-executable instructions that, when executed on one or more processors, performs the following: construct a first table user interface (UI) for display within a document including text and table, wherein the table supports full spreadsheet functionality; create a first cell table to hold data for the first table UI; construct a second table user interface (UI) for display within the document; create a second cell table to hold a formula for the second table UI, the formula referencing the data in the first cell table; upon modification of the data in the first cell table, automatically recalculate the formula in the second cell table to produce a new result; and providing a document behavior operation including one or more of spell checking, grammar checking, find, replace, and text formatting, across table boundaries, such that when invoked, document behavior operations that are applied to the text outside of the table are applied across a table boundary to text inside the table. 22. The computer medium of claim 21 , wherein the first table UI is nested within the second table UI.
| 0.547826 |
1. A method for managing and rendering one or more information nodes relative to a current focus, the method comprising: receiving, by a processor, one or more principal topics from a content of one or more information nodes, wherein the one or more information nodes includes at least one first information node; determining, by a processor, a topic vector from a similarity of a content of the first information node to the one or more principal topics; creating, by a processor, a map from the topic vector to a storage location of the first information node; determining, by a processor, one or more current topics from a content of a second information node, wherein the second information node is an information node that has been accessed recently; determining, by a processor, a current focus vector from a similarity of the one or more current topics to each of the one or more principal topics; and rendering, by a processor, a representation of the current focus vector and a representation of the first information node according to a rendering algorithm, wherein the rendering algorithm determines a position and a size of the representation of the current focus vector and of the first information node.
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1. A method for managing and rendering one or more information nodes relative to a current focus, the method comprising: receiving, by a processor, one or more principal topics from a content of one or more information nodes, wherein the one or more information nodes includes at least one first information node; determining, by a processor, a topic vector from a similarity of a content of the first information node to the one or more principal topics; creating, by a processor, a map from the topic vector to a storage location of the first information node; determining, by a processor, one or more current topics from a content of a second information node, wherein the second information node is an information node that has been accessed recently; determining, by a processor, a current focus vector from a similarity of the one or more current topics to each of the one or more principal topics; and rendering, by a processor, a representation of the current focus vector and a representation of the first information node according to a rendering algorithm, wherein the rendering algorithm determines a position and a size of the representation of the current focus vector and of the first information node. 9. The method of claim 1 , wherein the one or more leading topics are received from a user.
| 0.634342 |
1. A learning device comprising: a feature-quantity extraction circuit that extracts a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; an acquisition circuit that acquires, from an external device, a transfer classifier for detecting the detection target; a weak-classification calculation circuit that calculates a classification result of the detection target according to a weak classifier for each learning image by substituting the feature quantity extracted by the feature-quantity extraction unit that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and a classifier generation circuit that generates a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers.
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1. A learning device comprising: a feature-quantity extraction circuit that extracts a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; an acquisition circuit that acquires, from an external device, a transfer classifier for detecting the detection target; a weak-classification calculation circuit that calculates a classification result of the detection target according to a weak classifier for each learning image by substituting the feature quantity extracted by the feature-quantity extraction unit that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and a classifier generation circuit that generates a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers. 6. The learning device according to claim 1 , wherein the detection target is a hand, and the learning device differentiates between hand orientations.
| 0.608619 |
21. A computer-implemented method for providing an interactive user interface comprising: establishing, using a processor of the computer, a stepwise dialog embodied in a VoiceXML module executing instructions in a defined order based on an execution algorithm associated with the VoiceXML module, the execution algorithm establishing an interactive dialog with a user, the instructions including objects for processing events in the dialog associated with speech prompting and messaging to the user in the interactive dialog, wherein establishing the stepwise dialog declares a first field and a second field to be filled with portions of an input from the user; providing a prompt to the user based on the execution algorithm using the VoiceXML module; receiving a user input that is a response to the prompt, the user input including a first portion having speech input from the user and a second portion having a dual-tone multi-frequency (DTMF) input from the user; and performing at least one object oriented operation embodied in a SALT module upon receiving the user input, wherein the at least one object oriented operation initializes a recognition event associating the speech portion of the user input with the first field and the DTMF portion of the user input with the second field.
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21. A computer-implemented method for providing an interactive user interface comprising: establishing, using a processor of the computer, a stepwise dialog embodied in a VoiceXML module executing instructions in a defined order based on an execution algorithm associated with the VoiceXML module, the execution algorithm establishing an interactive dialog with a user, the instructions including objects for processing events in the dialog associated with speech prompting and messaging to the user in the interactive dialog, wherein establishing the stepwise dialog declares a first field and a second field to be filled with portions of an input from the user; providing a prompt to the user based on the execution algorithm using the VoiceXML module; receiving a user input that is a response to the prompt, the user input including a first portion having speech input from the user and a second portion having a dual-tone multi-frequency (DTMF) input from the user; and performing at least one object oriented operation embodied in a SALT module upon receiving the user input, wherein the at least one object oriented operation initializes a recognition event associating the speech portion of the user input with the first field and the DTMF portion of the user input with the second field. 24. The method of claim 21 wherein performing the operation further initiates a first grammar associated with the first field and a second field grammar associated with the second field.
| 0.720487 |
1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, an unstructured text query comprising one or more n-grams, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more of the nodes based at least on a determined probability for each node that the node corresponds to at least one of the n-grams, each of the identified nodes matching at least a portion of one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified nodes, each of the identified edges matching at least a portion of one or more of the n-grams; generating one or more structured queries that each comprise the n-grams of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the structured queries for presentation to the first user.
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1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, an unstructured text query comprising one or more n-grams, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more of the nodes based at least on a determined probability for each node that the node corresponds to at least one of the n-grams, each of the identified nodes matching at least a portion of one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified nodes, each of the identified edges matching at least a portion of one or more of the n-grams; generating one or more structured queries that each comprise the n-grams of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the structured queries for presentation to the first user. 14. The method of claim 1 , further comprising presenting the one or more sent structured queries to the first user, wherein, for each sent structured query, one or more of the references of the sent structured query is highlighted as presented to indicate the reference corresponds to an identified node or an identified edge.
| 0.563756 |
8. A speech recognition system, comprising: a speech recognition server, the speech recognition server including a processor configured to, receive, via a sound signal receiver, a sound signal from a terminal, the sound signal being input through an input device of the terminal, recognize at least one recognized word during a recognition time period, the recognition time period being determined based on a time when recognition of the at least one recognized word is initiated, a time when recognition of the at least one recognized word is terminated, and an allowable time value added to the time when the recognition of the at least one recognized word is terminated, determine a word sequence corresponding to the sound signal and at least one candidate word for at least one word in the word sequence, the candidate word being selected from among the at least one recognized word by, selecting, from among the at least one recognized word, words that have a same starting time, and combining at least two of the recognized words to form the at least one candidate word, if some of the at least one candidate words have the same starting time and a shorter end time, generate a speech recognition result, the speech recognition result including the word sequence and the at least one candidate word, and provide the speech recognition result to the terminal, wherein the word sequence is displayed on the terminal such that the at least one word is visually distinguishable from other words of the word sequence, and in response to selection of the at least one word, the word sequence is displayed by sequentially replacing the at least one word with the at least one candidate word such that the different ones of the at least one candidate word may be substituted into the word sequence each time the at least one word is selected without displaying a list of the at least one candidate word.
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8. A speech recognition system, comprising: a speech recognition server, the speech recognition server including a processor configured to, receive, via a sound signal receiver, a sound signal from a terminal, the sound signal being input through an input device of the terminal, recognize at least one recognized word during a recognition time period, the recognition time period being determined based on a time when recognition of the at least one recognized word is initiated, a time when recognition of the at least one recognized word is terminated, and an allowable time value added to the time when the recognition of the at least one recognized word is terminated, determine a word sequence corresponding to the sound signal and at least one candidate word for at least one word in the word sequence, the candidate word being selected from among the at least one recognized word by, selecting, from among the at least one recognized word, words that have a same starting time, and combining at least two of the recognized words to form the at least one candidate word, if some of the at least one candidate words have the same starting time and a shorter end time, generate a speech recognition result, the speech recognition result including the word sequence and the at least one candidate word, and provide the speech recognition result to the terminal, wherein the word sequence is displayed on the terminal such that the at least one word is visually distinguishable from other words of the word sequence, and in response to selection of the at least one word, the word sequence is displayed by sequentially replacing the at least one word with the at least one candidate word such that the different ones of the at least one candidate word may be substituted into the word sequence each time the at least one word is selected without displaying a list of the at least one candidate word. 11. The system of claim 8 , wherein the processor selects, as the word sequence, a word sequence having a highest probability among probabilities of a plurality of word sequences matching the sound signal.
| 0.573267 |
10. A method for web mining at least one couplet part, the method comprising: processing, by a computer, a search term of a query, wherein the search term comprises a first sentence of a Chinese couplet using a search engine resulting in a search result, and wherein the Chinese couplet comprises the first sentence and a second sentence; parsing, by the computer, the search result resulting from the processing, wherein the parsing results in a snippet set that is selected from at least one sentence that matches the query and information associated with the query and a suggested new search term for a subsequent query; filtering, by the computer, the snippet set resulting in at least one candidate sentence for the Chinese couplet; and generating, by at least a support vector machine classifier, at least one new sentence suitable for the Chinese couplet from the at least one candidate sentence.
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10. A method for web mining at least one couplet part, the method comprising: processing, by a computer, a search term of a query, wherein the search term comprises a first sentence of a Chinese couplet using a search engine resulting in a search result, and wherein the Chinese couplet comprises the first sentence and a second sentence; parsing, by the computer, the search result resulting from the processing, wherein the parsing results in a snippet set that is selected from at least one sentence that matches the query and information associated with the query and a suggested new search term for a subsequent query; filtering, by the computer, the snippet set resulting in at least one candidate sentence for the Chinese couplet; and generating, by at least a support vector machine classifier, at least one new sentence suitable for the Chinese couplet from the at least one candidate sentence. 12. The method as recited in claim 10 wherein the filtering the snippet set comprises dividing up text in at least one snippet of the snippet set into sentences based on punctuation.
| 0.561607 |
72. In a data processing system, a method for archiving non-text objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including an non-text object and a text object into said system; automatically generating a first key word for said non-text object from said text object; generating a link for said first key word to said text object; adding said first key word and said link to said index; storing said document architecture envelope in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said non-text object if said first key word is found in said comparing step.
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72. In a data processing system, a method for archiving non-text objects in a document, comprising the steps of: loading an existing index into a data processing system; inputting a document architecture envelope including an non-text object and a text object into said system; automatically generating a first key word for said non-text object from said text object; generating a link for said first key word to said text object; adding said first key word and said link to said index; storing said document architecture envelope in said system; storing said index including said first key word in said system; entering a search term into said data processing system; comparing said search term with candidate key words in said index; and retrieving said non-text object if said first key word is found in said comparing step. 74. The method of claim 72, wherein said first key word is generated from highlighting a word string in said text object.
| 0.88573 |
4. The method of claim 1 , further comprising: repeating the accessing and the importing for each functional block of the circuit design; and integrating data from each database into a system database through a system integration tool, the integrating including assigning base address information to each functional block.
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4. The method of claim 1 , further comprising: repeating the accessing and the importing for each functional block of the circuit design; and integrating data from each database into a system database through a system integration tool, the integrating including assigning base address information to each functional block. 7. The method of claim 4 , further comprising: processing the data integrated into the system database to generate a software driver based on a system design defined by the data integrated into the system database.
| 0.873048 |
13. An apparatus for training a duration prediction model, comprising: an initial model generator configured to generate an initial duration prediction model with a plurality of attributes related to duration prediction and at least part of possible attribute combinations of said plurality of attributes, in which each of said plurality of attributes and said attribute combinations is included as an item; an importance calculator configured to calculate importance of each said item in said duration prediction model; an item deleting unit configured to delete the item having a lowest importance calculated; a model re-generator configured to re-generate a duration prediction model with remaining items after a deletion of said item deleting unit; and an optimization determining unit configured to determine whether said duration prediction model re-generated by said model re-generator is an optimal model.
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13. An apparatus for training a duration prediction model, comprising: an initial model generator configured to generate an initial duration prediction model with a plurality of attributes related to duration prediction and at least part of possible attribute combinations of said plurality of attributes, in which each of said plurality of attributes and said attribute combinations is included as an item; an importance calculator configured to calculate importance of each said item in said duration prediction model; an item deleting unit configured to delete the item having a lowest importance calculated; a model re-generator configured to re-generate a duration prediction model with remaining items after a deletion of said item deleting unit; and an optimization determining unit configured to determine whether said duration prediction model re-generated by said model re-generator is an optimal model. 17. The apparatus for training a duration prediction model according to claim 13 , wherein said importance calculator is configured to calculate the importance of each said item with F-test.
| 0.692157 |
10. The system of claim 8 , wherein the embedded graphic object is rendered in the document of the second application by generating a view interface, wherein the view interface combines the semantic data and the presentation data.
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10. The system of claim 8 , wherein the embedded graphic object is rendered in the document of the second application by generating a view interface, wherein the view interface combines the semantic data and the presentation data. 11. The system of claim 10 , wherein the view interface includes a shape property bag that indicates properties of shapes within the graphic object.
| 0.946789 |
1. A method for controlling the execution of a statement of interpreted computer language code, the method comprising the steps of: determining that a statement of computer language code is attempting execution or that there is an invocation request to execute a statement of computer language code; intercepting the statement or invocation request prior to execution of the computer language code; passing control to a script helper module associated with a script engine able to interpret the statement of computer language code if a script helper module is present; passing control to a boot-strap loader if a script helper module is not present, retrieving an address of an information block (IDD) associated with a script engine able to interpret the statement of computer language code, wherein the information block identifies a script helper module associated with the script engine, and loading the script helper module identified in the information block; accessing the interpreted language code using the script helper module; identifying origin information relating to the statement of computer language code; establishing a secure communications channel with an authorization component; sending the interpreted language code over the channel with the identified origin information; receiving a reply from the authorization component; passing the original statement of computer language code or invocation request to the script engine, if execution thereof is permitted; and canceling the attempting execution of invocation request, if execution of the code is not permitted.
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1. A method for controlling the execution of a statement of interpreted computer language code, the method comprising the steps of: determining that a statement of computer language code is attempting execution or that there is an invocation request to execute a statement of computer language code; intercepting the statement or invocation request prior to execution of the computer language code; passing control to a script helper module associated with a script engine able to interpret the statement of computer language code if a script helper module is present; passing control to a boot-strap loader if a script helper module is not present, retrieving an address of an information block (IDD) associated with a script engine able to interpret the statement of computer language code, wherein the information block identifies a script helper module associated with the script engine, and loading the script helper module identified in the information block; accessing the interpreted language code using the script helper module; identifying origin information relating to the statement of computer language code; establishing a secure communications channel with an authorization component; sending the interpreted language code over the channel with the identified origin information; receiving a reply from the authorization component; passing the original statement of computer language code or invocation request to the script engine, if execution thereof is permitted; and canceling the attempting execution of invocation request, if execution of the code is not permitted. 2. A method for controlling execution of a statement of interpreted computer language code as recited in claim 1 , wherein the information block (IDD) identifies a list of routines that must be intercepted.
| 0.558398 |
13. A computer readable storage device comprising instructions that when executed perform a method, comprising: configuring a text messaging pipeline to order two or more pipeline modules comprised in the text messaging pipeline, the ordering comprising ordering a non-translation module of the two or more pipeline modules in the text messaging pipeline and a translation module of the two or more pipeline modules in the text messaging pipeline such that execution of the non-translation module in relation to a text message is performed prior to execution of the translation module in relation to the text message based upon a determination that using the non-translation module prior to using the translation module results in a first use of resources and using the translation module prior to using the non-translation module results in a second use of resources, the first use of resources less than the second use of resources.
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13. A computer readable storage device comprising instructions that when executed perform a method, comprising: configuring a text messaging pipeline to order two or more pipeline modules comprised in the text messaging pipeline, the ordering comprising ordering a non-translation module of the two or more pipeline modules in the text messaging pipeline and a translation module of the two or more pipeline modules in the text messaging pipeline such that execution of the non-translation module in relation to a text message is performed prior to execution of the translation module in relation to the text message based upon a determination that using the non-translation module prior to using the translation module results in a first use of resources and using the translation module prior to using the non-translation module results in a second use of resources, the first use of resources less than the second use of resources. 15. The computer readable storage device of claim 13 , the method comprising determining that one or more pipeline modules of the two or more pipeline modules are digitally signed.
| 0.638191 |
32. The method of claim 31 , wherein determining a plurality of paragraph metrics regarding each of the identified paragraphs further comprises, for each identified paragraph, determining the amount of indentation for the first line of text in each identified paragraph.
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32. The method of claim 31 , wherein determining a plurality of paragraph metrics regarding each of the identified paragraphs further comprises, for each identified paragraph, determining the amount of indentation for the first line of text in each identified paragraph. 33. The method of claim 32 , wherein determining a plurality of paragraph metrics regarding each of the identified paragraphs further comprises, for each identified paragraph, determining the line height of the paragraph, the line height being the distance between the baselines of two consecutive lines of textual content in the paragraph.
| 0.8281 |
11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that receives indicia representative of a goal from the spreadsheet object component of the rule-based expert system; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal based learning examples into the business simulation in a structured, dynamic business simulation designed by a profiling component to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further provides the student with assistance in accomplishing the goal; (d) a code segment that analyzes the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal; and (e) a code segment that provides a linkage to a website of information to supplement the information stored in the spreadsheet object component to assist with achieving the goal.
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11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a goal based educational environment, comprising: (a) a code segment that receives indicia representative of a goal from the spreadsheet object component of the rule-based expert system; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal based learning examples into the business simulation in a structured, dynamic business simulation designed by a profiling component to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further provides the student with assistance in accomplishing the goal; (d) a code segment that analyzes the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal; and (e) a code segment that provides a linkage to a website of information to supplement the information stored in the spreadsheet object component to assist with achieving the goal. 17. A computer program embodied on a computer-readable medium that creates a business simulation as recited in claim 11, wherein the information content of the website is indexed in a hierarchical manner.
| 0.503731 |
13. A system comprising: a database for storing names and affixes to names; a display for returning a result list comprised of the plurality of second values selected from the database; and a computing device for: receiving a name as a first character input string into only one input field, the name comprising an affix and at least one of a first name, a middle name, and a last name; parsing the first character input string taken from the one input field into a plurality of permutations of the input string; in response to the parsing, creating a lookup table having each of the plurality of permutations of the name parsed from the first character input string; iterating through the lookup table, the lookup table having an index value associated with each of the plurality of permutations of the name, the index value pointing to a next entry in the lookup table, wherein the customizing table contains affixes that are common in persons names; based on a comparison between the permutation of the input string in the lookup table and a customizing table, selecting first values from the customizing table including a second character input string related to the name permutation on the iteration of the lookup table, wherein the customizing table contains affixes that are common in persons names; identifying a next entry in the lookup table using an index value associated with the permutation of the name associated to the selected first value according to the comparison to the customizing table, if the index value of the identified next entry is an exit condition, exit the comparison of the customizing table; if the identified next entry has an index value assigned to a permutation of the input string, making a comparison between the next entry from the lookup table and the customizing table, selecting second values from the customizing table based on a result of the comparison; searching the database for the name input into the input field using, if the index value of the identified next entry was an exit condition, the selected first value, otherwise, using the selected first and second values; returning a result list comprised of the first values and the second values selected from the database; and presenting the result list to the display device.
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13. A system comprising: a database for storing names and affixes to names; a display for returning a result list comprised of the plurality of second values selected from the database; and a computing device for: receiving a name as a first character input string into only one input field, the name comprising an affix and at least one of a first name, a middle name, and a last name; parsing the first character input string taken from the one input field into a plurality of permutations of the input string; in response to the parsing, creating a lookup table having each of the plurality of permutations of the name parsed from the first character input string; iterating through the lookup table, the lookup table having an index value associated with each of the plurality of permutations of the name, the index value pointing to a next entry in the lookup table, wherein the customizing table contains affixes that are common in persons names; based on a comparison between the permutation of the input string in the lookup table and a customizing table, selecting first values from the customizing table including a second character input string related to the name permutation on the iteration of the lookup table, wherein the customizing table contains affixes that are common in persons names; identifying a next entry in the lookup table using an index value associated with the permutation of the name associated to the selected first value according to the comparison to the customizing table, if the index value of the identified next entry is an exit condition, exit the comparison of the customizing table; if the identified next entry has an index value assigned to a permutation of the input string, making a comparison between the next entry from the lookup table and the customizing table, selecting second values from the customizing table based on a result of the comparison; searching the database for the name input into the input field using, if the index value of the identified next entry was an exit condition, the selected first value, otherwise, using the selected first and second values; returning a result list comprised of the first values and the second values selected from the database; and presenting the result list to the display device. 15. A system according to claim 13 , wherein the index values are numbers used to determine the next string value to search in the lookup table if a current string value is not found in the customizing table.
| 0.5 |
15. The device of claim 14 , wherein each of the radio scenes detected at the portable electronic device at the respective predetermined reference time comprises a plurality of key-value pairs, each associated with the respective predetermined reference time the radio scene was detected at, wherein the executed instructions configure the device to further: access a plurality of key-value pairs, each comprising a respective key, corresponding to a unique transmitter identifier, and a value associated with a signal strength from the respective transmitter received at the portable electronic device at one of the plurality of respective predetermined reference times; and calculate each vector element based on a summation of a plurality of terms, each term calculated from a respective key-value pair by: generate a seed based on (i) the key of the respective key-value pair, (ii) an element identifier associated with the vector element being calculated and (iii) a reference time identifier of the respective predetermined reference time associated with the respective key-value pair.
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15. The device of claim 14 , wherein each of the radio scenes detected at the portable electronic device at the respective predetermined reference time comprises a plurality of key-value pairs, each associated with the respective predetermined reference time the radio scene was detected at, wherein the executed instructions configure the device to further: access a plurality of key-value pairs, each comprising a respective key, corresponding to a unique transmitter identifier, and a value associated with a signal strength from the respective transmitter received at the portable electronic device at one of the plurality of respective predetermined reference times; and calculate each vector element based on a summation of a plurality of terms, each term calculated from a respective key-value pair by: generate a seed based on (i) the key of the respective key-value pair, (ii) an element identifier associated with the vector element being calculated and (iii) a reference time identifier of the respective predetermined reference time associated with the respective key-value pair. 16. The device of claim 15 , wherein at least one of the keys of the plurality of key-value pairs is associated with one or more synonymous unique identifiers of transmitters located in close proximity to each other, wherein when the key of the respective key-value pair is associated with one or more synonymous unique identifiers, the term in the summation calculated by further adding one or more sub-terms, each calculated from a respective synonymous unique identifier of the one or more synonymous unique identifiers associated with the key of the respective key-value pair by: generating a synonym seed based on (i) the respective synonymous unique identifier (ii) the element identifier associated with the vector element being calculated and (iii) the reference time identifier of the respective predetermined reference time associated with the respective key-value pair; generating a synonym pseudo-random number from the generated synonym seed; and multiplying the synonym pseudo-random number by the value of the respective key-value pair.
| 0.589175 |
11. A computer program embodied on a non-transitory computer-readable storage medium and comprising code, that, when executed by a computer system, enables the computer system to perform the following method: receiving a call from a user at an IVR system; receiving a request from the user to speak with a live agent; queuing the user for a live agent; prompting the user to state a query; recording the user's speech input for the query; providing the user's query to a natural language understanding interpreter; receiving a natural language interpretation result; using the natural language interpretation result, determining if the user's query matches a query in a database that includes frequently-asked queries and corresponding response protocols; in response the user's query matching a query in the database, providing an automated response to the user in accordance with a predetermined response protocol for the query and asking the user if the user still desires to speak with a live agent; in response to the user's query not matching a query in the database or in response to the user indicating that the user still desires to speak with a live agent, transferring the user to a live agent; in response to the user being transferred to a live agent and after the live agent provides the user with a response to the user's query, prompting the user for feedback on the live agent's response, grading the live agent's response based on the user's feedback, and storing the live agent's response in association with the grade; and selecting a new response protocol for the query based at least in part on the grades associated with live agents' responses to the query.
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11. A computer program embodied on a non-transitory computer-readable storage medium and comprising code, that, when executed by a computer system, enables the computer system to perform the following method: receiving a call from a user at an IVR system; receiving a request from the user to speak with a live agent; queuing the user for a live agent; prompting the user to state a query; recording the user's speech input for the query; providing the user's query to a natural language understanding interpreter; receiving a natural language interpretation result; using the natural language interpretation result, determining if the user's query matches a query in a database that includes frequently-asked queries and corresponding response protocols; in response the user's query matching a query in the database, providing an automated response to the user in accordance with a predetermined response protocol for the query and asking the user if the user still desires to speak with a live agent; in response to the user's query not matching a query in the database or in response to the user indicating that the user still desires to speak with a live agent, transferring the user to a live agent; in response to the user being transferred to a live agent and after the live agent provides the user with a response to the user's query, prompting the user for feedback on the live agent's response, grading the live agent's response based on the user's feedback, and storing the live agent's response in association with the grade; and selecting a new response protocol for the query based at least in part on the grades associated with live agents' responses to the query. 15. The computer program of claim 11 , wherein the automated response to the user in accordance with the predetermined response protocol is provided via a voice interface.
| 0.580603 |
5. A non-transitory computer-readable medium, having stored thereon a sequence of instructions, which when executed by a computer, cause the computer to perform a method for generating a finite state grammar, the method comprising: (a) receiving user input of a plurality of sample phrases each comprising a plurality of words; (b) representing each sample phrase as a node in a tree; (c) forming a mathematical expression for each pair of nodes in the tree to represent the sample phrases associated with the pair of nodes, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; (d) generating a compact mathematical expression by comparing the mathematical expressions one pair at a time, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word; (e) displaying the compact mathematical expression to a user; (f) allowing the user to alter the compact mathematical expression; (g) generating a finite state grammar corresponding to the altered compact mathematical expression; and (h) displaying the finite state grammar to the user.
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5. A non-transitory computer-readable medium, having stored thereon a sequence of instructions, which when executed by a computer, cause the computer to perform a method for generating a finite state grammar, the method comprising: (a) receiving user input of a plurality of sample phrases each comprising a plurality of words; (b) representing each sample phrase as a node in a tree; (c) forming a mathematical expression for each pair of nodes in the tree to represent the sample phrases associated with the pair of nodes, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; (d) generating a compact mathematical expression by comparing the mathematical expressions one pair at a time, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word; (e) displaying the compact mathematical expression to a user; (f) allowing the user to alter the compact mathematical expression; (g) generating a finite state grammar corresponding to the altered compact mathematical expression; and (h) displaying the finite state grammar to the user. 6. The non-transitory computer-readable medium of claim 5 , wherein steps (f) to (h) are performed multiple times.
| 0.763432 |
1. A method for rewriting queries, the method comprising the computer implemented steps of: examining a first query that references a relation to which a second query evaluates; wherein the second query defines an array and a first set of formulas that reference the array; wherein the array has one or more dimensions; wherein the first query includes one or more predicates; wherein the second query does not include the one or more predicates; determining whether one or more criteria for rewriting said first query or said second query are satisfied; if said one or more criteria for rewriting said first query or said second query are satisfied, then making, based on said one or more predicates included in said first query, modifications to said second query involving one or more predicate conditions; and generating a rewritten query based on the modifications to said second query; wherein the steps of the method are performed by one or more computing devices.
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1. A method for rewriting queries, the method comprising the computer implemented steps of: examining a first query that references a relation to which a second query evaluates; wherein the second query defines an array and a first set of formulas that reference the array; wherein the array has one or more dimensions; wherein the first query includes one or more predicates; wherein the second query does not include the one or more predicates; determining whether one or more criteria for rewriting said first query or said second query are satisfied; if said one or more criteria for rewriting said first query or said second query are satisfied, then making, based on said one or more predicates included in said first query, modifications to said second query involving one or more predicate conditions; and generating a rewritten query based on the modifications to said second query; wherein the steps of the method are performed by one or more computing devices. 10. The method of claim 1 , wherein: a dimension of said one or more dimensions corresponds to a dimension column in said relation; said one or more predicates includes a particular predicate that references said dimension column; each formula of said set of formulas has a right side and a left side; the step of making modifications to said second query involving one or more predicate conditions includes a means for making modifications to the second query when, for at least one formula of said set of formulas, a value of the dimension referenced by the left side is different than a value referenced on the right side for the dimension.
| 0.630753 |
1. A computer-implemented method for remediating one or more non-compliant computer systems in a network, the method comprising: receiving one or more compliance rules, wherein the rules include conditions for detecting whether a computer system violates the rule and remediation steps associated with each rule for restoring compliance of the computer system when it violates the rule; identifying the computer system; determining the compliance of the computer system with the compliance rules by checking the included conditions; when the computer system is determined to violate a compliance rule, performing the remediation steps associated with the violated compliance rule on the computer system; and after performing any remediation steps on the computer system, removing the received compliance rules from the computer system.
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1. A computer-implemented method for remediating one or more non-compliant computer systems in a network, the method comprising: receiving one or more compliance rules, wherein the rules include conditions for detecting whether a computer system violates the rule and remediation steps associated with each rule for restoring compliance of the computer system when it violates the rule; identifying the computer system; determining the compliance of the computer system with the compliance rules by checking the included conditions; when the computer system is determined to violate a compliance rule, performing the remediation steps associated with the violated compliance rule on the computer system; and after performing any remediation steps on the computer system, removing the received compliance rules from the computer system. 4. The method of claim 1 wherein identifying the computer system comprises crawling the network with a spider application.
| 0.601004 |
1. A method comprising: classifying a reference set of visual patterns that belong to a parent class into mutually exclusive child classes that include first and second child classes, a visual pattern from the reference set being classified into the first child class instead of the second child class; modifying a weight vector that corresponds to the parent class, the modified weight vector altering a first probability that the visual pattern belongs to the first child class and a second probability that the visual pattern belongs to the second child class; based on the altered first and second probabilities, removing mutual exclusivity from the first and second child classes by adding the visual pattern to the second child class; and using a processor, generating a hierarchy of classes of visual patterns, the hierarchy including the parent class and the mutually nonexclusive first and second child classes that each include the visual pattern.
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1. A method comprising: classifying a reference set of visual patterns that belong to a parent class into mutually exclusive child classes that include first and second child classes, a visual pattern from the reference set being classified into the first child class instead of the second child class; modifying a weight vector that corresponds to the parent class, the modified weight vector altering a first probability that the visual pattern belongs to the first child class and a second probability that the visual pattern belongs to the second child class; based on the altered first and second probabilities, removing mutual exclusivity from the first and second child classes by adding the visual pattern to the second child class; and using a processor, generating a hierarchy of classes of visual patterns, the hierarchy including the parent class and the mutually nonexclusive first and second child classes that each include the visual pattern. 14. The method of claim 1 , wherein: the modified weight vector includes a third probability that the visual pattern belongs to a third child class of the parent class; and the removing of mutual exclusivity from the first and second child classes is further based on the third probability falling outside of a predetermined subset of largest probabilities that the visual pattern belongs to one of the mutually exclusive child classes.
| 0.526639 |
22. A system comprising: one or more processors; one or more storage media storing instructions which, when executed by the one or more processors, cause: storing a plurality of multi-language profiles of a plurality of users; identifying one or more multilingual cognates in each profile of the plurality of multi-language profiles; based on the one or more multilingual cognates identified in each profile of the plurality of multi-language profiles, generating one or more translation models; receiving input that indicates a selection, by a second user, of data that is associated with a first user that is different than the second user, wherein the plurality of users includes users other than the second user and the first user; determining a first language that is associated with the first user; determining a second language that is different than the first language and that is associated with the second user; wherein a plurality of data items in a profile of the first user are in the first language; translating the plurality of data items into the second language using the one or more translation models; in response to receiving the input, causing a translated version of the plurality of data items to be displayed to the second user, wherein the translated version is in the second language.
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22. A system comprising: one or more processors; one or more storage media storing instructions which, when executed by the one or more processors, cause: storing a plurality of multi-language profiles of a plurality of users; identifying one or more multilingual cognates in each profile of the plurality of multi-language profiles; based on the one or more multilingual cognates identified in each profile of the plurality of multi-language profiles, generating one or more translation models; receiving input that indicates a selection, by a second user, of data that is associated with a first user that is different than the second user, wherein the plurality of users includes users other than the second user and the first user; determining a first language that is associated with the first user; determining a second language that is different than the first language and that is associated with the second user; wherein a plurality of data items in a profile of the first user are in the first language; translating the plurality of data items into the second language using the one or more translation models; in response to receiving the input, causing a translated version of the plurality of data items to be displayed to the second user, wherein the translated version is in the second language. 25. The system of claim 22 , wherein the instructions, when executed by the one or more processors, further cause: identifying a first user profile that includes a first plurality of data items in the first language and a second plurality of data items in the second language, wherein the first plurality of data items correspond to the second plurality of data items; identifying a second user profile that is different than the first user profile and that includes a third plurality of data items in the first language and a fourth plurality of data items in the second language, wherein the third plurality of data items correspond to the fourth plurality of data items; generating multilingual cognates based on a correspondence between the first plurality of data items and the second plurality of data items and based on a correspondence between the third plurality of data items and the fourth plurality of data items.
| 0.5 |
36. A method for controlling a cooking oven having means defining an oven cavity, heating means for heating said oven cavity to defined heating temperatures, including the steps of: prompting a user input selection of a heating mode from one of a cooking mode and a cleaning mode; prompting a user input entry of a heating temperature for said oven cavity and displaying the entered heating temperature; prompting a user selection of up to two timing modes independently of the selected heating mode; prompting a user entry of time values for the selected timing modes and displaying the entered time values; wherein said prompting and said displaying steps define at least a portion of a grammatical sentence to the user; establishing a time and temperature heating profile of said oven cavity from the selected heating function and timing functions and entered heating temperature and time values; and controlling said heating means according to said heating profile.
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36. A method for controlling a cooking oven having means defining an oven cavity, heating means for heating said oven cavity to defined heating temperatures, including the steps of: prompting a user input selection of a heating mode from one of a cooking mode and a cleaning mode; prompting a user input entry of a heating temperature for said oven cavity and displaying the entered heating temperature; prompting a user selection of up to two timing modes independently of the selected heating mode; prompting a user entry of time values for the selected timing modes and displaying the entered time values; wherein said prompting and said displaying steps define at least a portion of a grammatical sentence to the user; establishing a time and temperature heating profile of said oven cavity from the selected heating function and timing functions and entered heating temperature and time values; and controlling said heating means according to said heating profile. 37. The method in claim 36 wherein said grammatical sentence portion corresponds with cooking recipe instructions.
| 0.787225 |
7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components.
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7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components. 9. The method according to claim 7 , wherein specifying the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service further comprises specifying the particular grid component to interpret the aspect of a clothing style by detecting at least one word indicating a particular clothing style and returning an interpreted meaning comprising a plurality of words describing the particular clothing style.
| 0.559758 |
1. A computer-implemented method for identifying search terms for advertising an item, the method comprising: identifying the item proposed for advertising; submitting a description of the item to a search engine service; receiving search results provided by the search engine service corresponding to the description of the item; analyzing web pages corresponding to the received search results to identify phrases of words within the web pages that are related to the item, the identifying of the phrases including generating a first score for at least some of the words of the web pages and generating a second score for phrases based at least in part on the first score of said at least some of the words within the phrases; the first score being generated based at least in part on a relative value of: a first average frequency of the word in the web pages, said first average frequency based at least in part upon a first frequency of the word for a plurality of the web pages corresponding to the received search results; a second average frequency of the word in a general corpus of web pages, said second average frequency based at least in part upon a second frequency of the word for the general corpus of web pages; the relative value of the first average frequency with respect to the second average frequency indicating a level of relevance of the word to the item; and deriving search terms for advertising the item from the identified phrases of the search results based at least in part upon the second score for each of the identified phrases.
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1. A computer-implemented method for identifying search terms for advertising an item, the method comprising: identifying the item proposed for advertising; submitting a description of the item to a search engine service; receiving search results provided by the search engine service corresponding to the description of the item; analyzing web pages corresponding to the received search results to identify phrases of words within the web pages that are related to the item, the identifying of the phrases including generating a first score for at least some of the words of the web pages and generating a second score for phrases based at least in part on the first score of said at least some of the words within the phrases; the first score being generated based at least in part on a relative value of: a first average frequency of the word in the web pages, said first average frequency based at least in part upon a first frequency of the word for a plurality of the web pages corresponding to the received search results; a second average frequency of the word in a general corpus of web pages, said second average frequency based at least in part upon a second frequency of the word for the general corpus of web pages; the relative value of the first average frequency with respect to the second average frequency indicating a level of relevance of the word to the item; and deriving search terms for advertising the item from the identified phrases of the search results based at least in part upon the second score for each of the identified phrases. 2. The method of claim 1 , further comprising retrieving the description from an item catalog.
| 0.571311 |
31. The at least one non-transitory computer-readable medium of claim 29 , comprising: a grant element specifying a permission that a principal may perform an act, whereby a computer system can enforce at least one of said permission based on said grant element by verifying that said principal may perform said act, said intention based on said intent element by verifying that said principal wants to perform said act, and said assertion based on said claim element by verifying that said principal does perform said act.
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31. The at least one non-transitory computer-readable medium of claim 29 , comprising: a grant element specifying a permission that a principal may perform an act, whereby a computer system can enforce at least one of said permission based on said grant element by verifying that said principal may perform said act, said intention based on said intent element by verifying that said principal wants to perform said act, and said assertion based on said claim element by verifying that said principal does perform said act. 34. The at least one non-transitory computer-readable medium of claim 31 , comprising: respective act elements as attributes associated with said duty element, said ban element, said grant element, said intent element, and said claim element, and specifying the respective acts.
| 0.744261 |
16. A computer-readable medium storage device comprising computer-executable instructions that, when executed by a processor, cause a computing device to perform a method for testing a component of a database application, the method comprising: populating, as specified by a user, a column in a database with test data that falls within a certain range specified by the user; specifying, by the user, a desired cardinality constraint suitable for testing the component, the component operating on a computing device, wherein the component is a software component; specifying, by the user, a parametric pattern query that includes a parameter, wherein the parametric pattern query is compatible with the database, and wherein the parametric pattern query is configured to restrict cardinality when evaluated against the database; selecting a candidate value; evaluating, by the computing device via the component, the parametric pattern query against the database with the parameter set to the candidate value; calculating, by the computing device, a cardinality error as a difference between a returned cardinality and the desired cardinality constraint wherein the returned cardinality results from the evaluating; and adjusting the candidate value based on the calculated cardinality error and then repeating the evaluating the parametric pattern query against the database with the parameter set to the adjusted candidate value and the calculating the cardinality error until the calculated cardinality error is within an allowable limit.
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16. A computer-readable medium storage device comprising computer-executable instructions that, when executed by a processor, cause a computing device to perform a method for testing a component of a database application, the method comprising: populating, as specified by a user, a column in a database with test data that falls within a certain range specified by the user; specifying, by the user, a desired cardinality constraint suitable for testing the component, the component operating on a computing device, wherein the component is a software component; specifying, by the user, a parametric pattern query that includes a parameter, wherein the parametric pattern query is compatible with the database, and wherein the parametric pattern query is configured to restrict cardinality when evaluated against the database; selecting a candidate value; evaluating, by the computing device via the component, the parametric pattern query against the database with the parameter set to the candidate value; calculating, by the computing device, a cardinality error as a difference between a returned cardinality and the desired cardinality constraint wherein the returned cardinality results from the evaluating; and adjusting the candidate value based on the calculated cardinality error and then repeating the evaluating the parametric pattern query against the database with the parameter set to the adjusted candidate value and the calculating the cardinality error until the calculated cardinality error is within an allowable limit. 20. The computer-readable medium of claim 16 , wherein, in response to the cardinality error being within the allowable limit, the parametric pattern query with the parameter set to the candidate value or the adjusted candidate value is utilized to test the component.
| 0.673192 |
1. A computer-implemented method, comprising: receiving a recommendation of a person from an expertise discovery function executed on a processor-based device that generates the recommendation in accordance with an inference of a level of expertise from a plurality of usage behaviors; and receiving an explanation from a computer-implemented explanatory function, wherein the explanation comprises a reason as to why the person was recommended.
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1. A computer-implemented method, comprising: receiving a recommendation of a person from an expertise discovery function executed on a processor-based device that generates the recommendation in accordance with an inference of a level of expertise from a plurality of usage behaviors; and receiving an explanation from a computer-implemented explanatory function, wherein the explanation comprises a reason as to why the person was recommended. 2. The method of claim 1 , further comprising: receiving the recommendation of a person from the expertise discovery function executed on a processor-based device that generates the recommendation in accordance with the inference of a level of expertise from a plurality of usage behaviors, wherein the inference is in accordance with a specified topical neighborhood.
| 0.508152 |
17. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, from a user device of a first user, a media object and a query associated with the media object, wherein the query requests information related to content presented in the media object; providing for presentation the media object and the query to a plurality of second users different from the first user; receiving a suggested answer to the query from one or more second users of the plurality of second users, wherein a suggested answer from a particular second user is either (i) a new suggested answer submitted by the particular second user in response to the query or (ii) associated with a previous suggested answer to the query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the query; and providing for presentation one or more of the suggested answers to the first user.
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17. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, from a user device of a first user, a media object and a query associated with the media object, wherein the query requests information related to content presented in the media object; providing for presentation the media object and the query to a plurality of second users different from the first user; receiving a suggested answer to the query from one or more second users of the plurality of second users, wherein a suggested answer from a particular second user is either (i) a new suggested answer submitted by the particular second user in response to the query or (ii) associated with a previous suggested answer to the query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the query; and providing for presentation one or more of the suggested answers to the first user. 18. The computer storage medium of claim 17 wherein the suggested answer associated with the previous suggested answer to the query is derived from the previous suggested answer.
| 0.632091 |
1. A method of comparing a first document and a second document, wherein the text of each of the first and second documents can be divided up into basic units, the method comprising: generating a first sequence of images of basic units from the first document; generating a second sequence of images of basic units from the second document, wherein the basic unit images of the first sequence and the second sequence include characters, words, lines, or paragraphs; comparing the basic unit images of the first sequence with the basic unit images of the second sequence to identify matches between the basic unit images of the first sequence and the second sequence and identify differences between the basic unit images of the first sequence and the second sequence, wherein the comparing includes: calculating a coarse distance measure between the basic unit images of the first sequence and the second sequence to align the basic unit images; and calculating a fine distance measure between aligned basic unit images of the first sequence and the second sequence to identify differences between the aligned basic unit images of the first sequence and the second sequence, wherein the fine distance measure is performed at a higher resolution than the coarse distance measure; and outputting information about the differences between the first document and the second document.
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1. A method of comparing a first document and a second document, wherein the text of each of the first and second documents can be divided up into basic units, the method comprising: generating a first sequence of images of basic units from the first document; generating a second sequence of images of basic units from the second document, wherein the basic unit images of the first sequence and the second sequence include characters, words, lines, or paragraphs; comparing the basic unit images of the first sequence with the basic unit images of the second sequence to identify matches between the basic unit images of the first sequence and the second sequence and identify differences between the basic unit images of the first sequence and the second sequence, wherein the comparing includes: calculating a coarse distance measure between the basic unit images of the first sequence and the second sequence to align the basic unit images; and calculating a fine distance measure between aligned basic unit images of the first sequence and the second sequence to identify differences between the aligned basic unit images of the first sequence and the second sequence, wherein the fine distance measure is performed at a higher resolution than the coarse distance measure; and outputting information about the differences between the first document and the second document. 8. A method according to claim 1 wherein the comparing includes: identifying matches between the basic unit images of the first and second sequences, wherein the identifying matches includes minimising a global distance measure as a sum of coarse local distance measures for the basic unit images of the first and second sequences, the coarse local distance measure being a measure of the difference between the basic unit image of the first sequence and the basic unit image of the second sequence.
| 0.594534 |
1. A computer-implemented method of detecting a bad faith essay response, the method comprising: receiving a plurality of essay prompts with a computer; receiving an essay response in the computer associated with a particular essay prompt of the plurality of essay prompts; scoring by the computer the essay response associated with the particular essay prompt against each of the plurality of essay prompts to generate plural similarity scores; and determining by the computer if the essay response associated with the particular essay prompt is a bad faith essay response based at least in part on determining whether the plural similarity scores indicate that the essay response associated with the particular essay prompt is sufficiently dissimilar to each of the plurality of essay prompts.
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1. A computer-implemented method of detecting a bad faith essay response, the method comprising: receiving a plurality of essay prompts with a computer; receiving an essay response in the computer associated with a particular essay prompt of the plurality of essay prompts; scoring by the computer the essay response associated with the particular essay prompt against each of the plurality of essay prompts to generate plural similarity scores; and determining by the computer if the essay response associated with the particular essay prompt is a bad faith essay response based at least in part on determining whether the plural similarity scores indicate that the essay response associated with the particular essay prompt is sufficiently dissimilar to each of the plurality of essay prompts. 5. The method of claim 1 , wherein determining if the essay response associated with the particular essay prompt is a bad faith essay response is carried out without utilizing training essays on a topic for the particular essay prompt.
| 0.766337 |
8. The device of claim 1 , wherein the set of words includes a plurality of words.
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8. The device of claim 1 , wherein the set of words includes a plurality of words. 10. The device of claim 8 , wherein the expansion means is adapted to act on each word individually, the conversion means further including means for writing each further pair of consecutive words, including a further word to be expanded, into the second memory area separated by a number of locations corresponding to the additional symbols to be added to the further word.
| 0.852246 |
10. The integration server system of claim 9 , wherein the database schema includes a class type attribute identifying each of the set of data object instances as a member of at least one of a plurality of classes.
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10. The integration server system of claim 9 , wherein the database schema includes a class type attribute identifying each of the set of data object instances as a member of at least one of a plurality of classes. 11. The integration server system of claim 10 , wherein the database constraint is conditioned on the value of the class type attribute.
| 0.962834 |
1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory.
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1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory. 10. The method of claim 1 , wherein determining the candidate n-gram score based on the first amount and the second amount comprises performing steps for determining the candidate n-gram score.
| 0.630805 |
15. A computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving audio data encoding an utterance, and data specifying a time when the utterance was spoken; determining, for each of multiple communications that were initiated by a user of a mobile device, a time when the communication was initiated or received; determining, for each of the multiple communications, a similarity score based on a similarity between the time when the communication was initiated or received, and the time when the utterance was spoken; determining, for each of multiple contacts associated with the user, a probability associated with the contact based at least on the similarity score for the communications that were initiated or received; weighting a contact disambiguation grammar according to the probabilities; and processing the audio data using the contact disambiguation grammar to select a particular contact.
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15. A computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving audio data encoding an utterance, and data specifying a time when the utterance was spoken; determining, for each of multiple communications that were initiated by a user of a mobile device, a time when the communication was initiated or received; determining, for each of the multiple communications, a similarity score based on a similarity between the time when the communication was initiated or received, and the time when the utterance was spoken; determining, for each of multiple contacts associated with the user, a probability associated with the contact based at least on the similarity score for the communications that were initiated or received; weighting a contact disambiguation grammar according to the probabilities; and processing the audio data using the contact disambiguation grammar to select a particular contact. 18. The device of claim 15 , wherein the operations comprise: receiving data specifying a device type of a mobile device used to obtain the utterance; determining, for each of the multiple communications that were initiated by the user of the mobile device, a device type of the mobile device used to initiate or receive the communication; and wherein the respective similarity score is determined further used on a similarity between the device type of the mobile device used to initiate or receive the communication, and the device type of the mobile device used to obtain the utterance.
| 0.56659 |
1. A system for automatically extracting relations between concepts included in electronic text, comprising: a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and a linguistic engine for performing semantic disambiguation on the electronic text using the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text.
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1. A system for automatically extracting relations between concepts included in electronic text, comprising: a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and a linguistic engine for performing semantic disambiguation on the electronic text using the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. 20. The system of claim 1 wherein the linguistic processor includes a sentence identification stage, a token extraction stage, a morphological and grammatical analysis stage, a sentence analysis stage, and a semantic disambiguation stage.
| 0.577113 |
1. A system that uses a combination of semantic and statistical processing of input or data content, comprising: a system including a computer having a processor and memory that receives an input in the form of a user-entered search query, a set of text retrieved by an automated robot process, web page, electronic document, or some other form of input; a semantically-enhanced statistical lookup data, which is created by analysis of a plurality of documents on various topics, to determine sufficient and necessary keyphrases, wherein a keyphrase is considered sufficient for a particular topic when if that keyphrase is found in the input, the input is likely to be in that topic, and a keyphrase is considered necessary for a particular topic when, if that keyphrase is found in the input, the input is both very likely to be in that topic, and very unlikely to be in any other topic; a semantically-enhanced comparison logic which uses the information in the semantically-enhanced statistical lookup data to analyze the input, compare search words in the input with keyphrases, determine an appropriate topic, and generate an appropriate output; and wherein keyphrases have an entropy associated therewith, wherein keyphrases that are sufficient for a particular topic have a relatively lower entropy than keyphrases that are sufficient for several topics, and a relatively higher entropy than keyphrases that are necessary for the particular topic; and wherein for a particular topic, the set of necessary keyphrases are a subset of sufficient keyphrases for that topic.
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1. A system that uses a combination of semantic and statistical processing of input or data content, comprising: a system including a computer having a processor and memory that receives an input in the form of a user-entered search query, a set of text retrieved by an automated robot process, web page, electronic document, or some other form of input; a semantically-enhanced statistical lookup data, which is created by analysis of a plurality of documents on various topics, to determine sufficient and necessary keyphrases, wherein a keyphrase is considered sufficient for a particular topic when if that keyphrase is found in the input, the input is likely to be in that topic, and a keyphrase is considered necessary for a particular topic when, if that keyphrase is found in the input, the input is both very likely to be in that topic, and very unlikely to be in any other topic; a semantically-enhanced comparison logic which uses the information in the semantically-enhanced statistical lookup data to analyze the input, compare search words in the input with keyphrases, determine an appropriate topic, and generate an appropriate output; and wherein keyphrases have an entropy associated therewith, wherein keyphrases that are sufficient for a particular topic have a relatively lower entropy than keyphrases that are sufficient for several topics, and a relatively higher entropy than keyphrases that are necessary for the particular topic; and wherein for a particular topic, the set of necessary keyphrases are a subset of sufficient keyphrases for that topic. 3. The system of claim 1 , wherein the semantically-enhanced statistical lookup data includes a plurality of entries, including for each of a plurality of topics a plurality of keyphrases associated with that topic, together with an indication or factor as to whether that keyphrase is sufficient and whether that keyphrase is necessary, and optionally an indication or factor as to the keyphrase's entropy.
| 0.562153 |
1. A method of selectively interpreting or translating program code in a computing environment having a target processor and a memory coupled to the target processor, the program code comprising instructions from the instruction set of a subject processor, the method comprising: decoding said program code; applying an interpreting algorithm to identify whether said program code is interpretable by a simple interpreter, said simple interpreter incapable of interpreting a subset of instructions from the instruction set of the subject processor; if said program code contains only instructions in the subset such that the program code is interpretable by the simple interpreter, interpreting the program code using the simple interpreter; and translating said program code using a translator for non-interpretable subset of instructions when said program code is not interpreted.
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1. A method of selectively interpreting or translating program code in a computing environment having a target processor and a memory coupled to the target processor, the program code comprising instructions from the instruction set of a subject processor, the method comprising: decoding said program code; applying an interpreting algorithm to identify whether said program code is interpretable by a simple interpreter, said simple interpreter incapable of interpreting a subset of instructions from the instruction set of the subject processor; if said program code contains only instructions in the subset such that the program code is interpretable by the simple interpreter, interpreting the program code using the simple interpreter; and translating said program code using a translator for non-interpretable subset of instructions when said program code is not interpreted. 8. The method of claim 1 , wherein the step of applying an interpreting algorithm to identify whether the program code is interpretable further comprises determining whether an execution count of the program code is below a translation threshold, wherein the program code is translated by the translator if the execution count of the program code is greater than or equal to the translation threshold.
| 0.550227 |
6. The computer implemented method according to claim 5 , wherein said writing further comprises: writing out said multiple target modules in said multiple target programming languages.
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6. The computer implemented method according to claim 5 , wherein said writing further comprises: writing out said multiple target modules in said multiple target programming languages. 7. The computer implemented method according to claim 6 , wherein said source programming language is different from each of said multiple target programming languages selected.
| 0.950231 |
12. A computer system for identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment are determined by the computer by identifying one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: analyzing, by the computer, the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; assigning, by the computer, one or more features to the one or more variations by selecting, by the computer, a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of a sound wave having a sound wave contour between silences; mapping, by the computer, one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of word; determining, by the computer, parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; grouping, by the computer, the parameters into predefined characteristics; combining, by the computer, the predefined characteristics into a voice characteristic group; and comparing, by the computer, the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, by the computer, the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group.
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12. A computer system for identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment are determined by the computer by identifying one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: analyzing, by the computer, the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; assigning, by the computer, one or more features to the one or more variations by selecting, by the computer, a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of a sound wave having a sound wave contour between silences; mapping, by the computer, one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of word; determining, by the computer, parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; grouping, by the computer, the parameters into predefined characteristics; combining, by the computer, the predefined characteristics into a voice characteristic group; and comparing, by the computer, the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, by the computer, the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group. 14. The computer system of claim 12 , wherein the plurality of features comprises: feature 1 having a characteristic of the sound wave varying rapidly around the zero value in positive and negative half-waves; feature 2 having a characteristic of a slope_change count of the sound wave being greater than a slope_zero count in a half-wave; feature 3 having a characteristic of slope_zero count being greater than zero and slope_change count being equal to zero in a half-wave; feature 4 having a characteristic of slope_change count being greater than zero and slope_zero count being equal to zero in a half-wave; feature 5 having a characteristic of slope_zero count being greater than slope_change count in a half-wave; feature 6 having a characteristic of slope_positive count being greater than zero in a half-wave; feature 7 having a characteristic of a slope_change count of the sound wave being greater than a slope_zero count in a half-wave, wherein the slope_change count occurs prior to the slope_zero count in the half-wave; and feature 8 having a characteristic of slope_zero count being greater than slope_change count in a half-wave, wherein the slope_zero count occurs prior to the slope_change count in the half-wave.
| 0.509179 |
20. The semantic processor of claim 15 , wherein the one or more eSAO Whole-Part relations each comprises a Whole eSAO, a Part eSAO, and at least one sequential operator relating the Whole eSAO to the Part eSAO.
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20. The semantic processor of claim 15 , wherein the one or more eSAO Whole-Part relations each comprises a Whole eSAO, a Part eSAO, and at least one sequential operator relating the Whole eSAO to the Part eSAO. 21. The semantic processor of claim 20 , wherein each eSAO set based on the text comprises eSAO components and the Whole eSAO comprises one or more of the eSAO components and the Part eSAO comprises one or more of the eSAO components different than the one or more eSAO components of the Whole eSAO.
| 0.930037 |
1. A method comprising, by a computing device of a social-networking system: by the computing device, receiving, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; by the computing device, determining whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; by the computing device, parsing the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; by the computing device, generating a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; by the computing device, generating a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and by the computing device, sending, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user.
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1. A method comprising, by a computing device of a social-networking system: by the computing device, receiving, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; by the computing device, determining whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; by the computing device, parsing the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; by the computing device, generating a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; by the computing device, generating a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and by the computing device, sending, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user. 17. The method of claim 1 , wherein presenting the one or more of the plurality of search results comprises displaying the one or more of the plurality of search results to the user in a notification user interface in association with the unstructured query.
| 0.574462 |
3. The mobile device of claim 1 wherein the controller determines whether the audible speech has a high recognition uncertainty.
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3. The mobile device of claim 1 wherein the controller determines whether the audible speech has a high recognition uncertainty. 6. The mobile device of claim 3 wherein the controller sends the phonemes via the transmitter based upon the determination that the audible speech has high recognition uncertainty.
| 0.883075 |
12. A computer-readable storage device having computer-executable instructions stored thereon, which when executed perform acts, comprising: for each of a set of data items relating to experiences of a human user of a computing device, enabling at least one processor to iteratively obtain and store values of a selected subset of the set of data items, each stored value of a data item being stored with an indication of the data item and an indication of an effective time of the stored value, at least one data item obtaining values from a plurality of data sources, the data sources comprising at least one of a source of geographic information and physiological information; enabling the at least one processor to receive, from at least one application that performs logged context attribute analysis, a specification for analyzing values among the stored values that specifies one or more data items, a range of effective times, and an analysis technique applicable to the data items, the analysis technique includes determining a result that would have been produced had a rule been applied to analyze the specified context attribute values at the time the values were generated, the rule configured for analyzing context attribute values in real-time to produce a result, the rule adopted for future real-time application when it is determined that a successful result would have been produced had the rule been applied to analyze the specified context attribute values at the time the values were generated; enabling the at least one processor to retrieve stored values for the specified data items within the specified range of effective times and retrieving the real time values for the remaining non-specified data items; enabling the at least one processor to apply the specified analysis technique to the retrieved values using the specified one or more context attributes to produce an analysis of experiences of the human user; and enabling the at least one processor to select an operating characteristic of the computing device based on inferring a current or future status of the human user based on the analysis of experiences of the human user.
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12. A computer-readable storage device having computer-executable instructions stored thereon, which when executed perform acts, comprising: for each of a set of data items relating to experiences of a human user of a computing device, enabling at least one processor to iteratively obtain and store values of a selected subset of the set of data items, each stored value of a data item being stored with an indication of the data item and an indication of an effective time of the stored value, at least one data item obtaining values from a plurality of data sources, the data sources comprising at least one of a source of geographic information and physiological information; enabling the at least one processor to receive, from at least one application that performs logged context attribute analysis, a specification for analyzing values among the stored values that specifies one or more data items, a range of effective times, and an analysis technique applicable to the data items, the analysis technique includes determining a result that would have been produced had a rule been applied to analyze the specified context attribute values at the time the values were generated, the rule configured for analyzing context attribute values in real-time to produce a result, the rule adopted for future real-time application when it is determined that a successful result would have been produced had the rule been applied to analyze the specified context attribute values at the time the values were generated; enabling the at least one processor to retrieve stored values for the specified data items within the specified range of effective times and retrieving the real time values for the remaining non-specified data items; enabling the at least one processor to apply the specified analysis technique to the retrieved values using the specified one or more context attributes to produce an analysis of experiences of the human user; and enabling the at least one processor to select an operating characteristic of the computing device based on inferring a current or future status of the human user based on the analysis of experiences of the human user. 16. The computer-readable storage device of claim 12 , wherein said enabling the at least one processor to store values of the selected subset of the set of data items comprises: enabling the at least one processor to store the values in a sparse matrix.
| 0.545781 |
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