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15. The computer-implemented method of claim 13 , wherein the select expression is a numeric expression to select fact data.
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15. The computer-implemented method of claim 13 , wherein the select expression is a numeric expression to select fact data. 16. The computer-implemented method of claim 15 , wherein the numeric expression defines a calculation that is independent of a binding of the query object to a data source.
| 0.91645 |
7. A signal tagging system, comprising: a processor; a classifier module configured to control the processor to accept an input data signal wherein the classifier module classifies the input data signal into one of at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also is configured to bypass data that is known to be of no interest; a collapser module further configured to control the processor to collapse the input data that is classified as having no identified outputs, thereby creating time-variant data; and a signal tagger configured to control the processor to tag known signals of interest within the time-variant data classified as having at least one potential signal of interest.
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7. A signal tagging system, comprising: a processor; a classifier module configured to control the processor to accept an input data signal wherein the classifier module classifies the input data signal into one of at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also is configured to bypass data that is known to be of no interest; a collapser module further configured to control the processor to collapse the input data that is classified as having no identified outputs, thereby creating time-variant data; and a signal tagger configured to control the processor to tag known signals of interest within the time-variant data classified as having at least one potential signal of interest. 8. The signal tagging system of claim 7 , wherein the signal tagger is further configured to tag the time variant data as one of a known signal of interest or a potential signal of interest.
| 0.560319 |
1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a first keyboard on the display, the first keyboard comprising a first plurality of keys; detecting a key activation gesture at a first time at a location on the touch-sensitive surface that corresponds to a location of a first key in the first keyboard; in response to detecting the key activation gesture at the first time, activating the first key; detecting one or more contacts on the touch-sensitive surface at a second time after the first time, the one or more contacts corresponding to a keyboard selection gesture; and, in response to detecting the one or more contacts that correspond to the keyboard selection gesture at the second time after the first time: replacing the first keyboard with a second keyboard when the second time exceeds a predefined period of time after the first time; and maintaining display of the first keyboard when the second time is less than the predefined period of time after the first time.
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1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a first keyboard on the display, the first keyboard comprising a first plurality of keys; detecting a key activation gesture at a first time at a location on the touch-sensitive surface that corresponds to a location of a first key in the first keyboard; in response to detecting the key activation gesture at the first time, activating the first key; detecting one or more contacts on the touch-sensitive surface at a second time after the first time, the one or more contacts corresponding to a keyboard selection gesture; and, in response to detecting the one or more contacts that correspond to the keyboard selection gesture at the second time after the first time: replacing the first keyboard with a second keyboard when the second time exceeds a predefined period of time after the first time; and maintaining display of the first keyboard when the second time is less than the predefined period of time after the first time. 6. The device of claim 1 , wherein replacing the first keyboard with the second keyboard includes displaying an animation that transitions the first keyboard to the second keyboard.
| 0.551487 |
27. In the document structure of claim 26 and wherein: the means for identifying the type and start of the descriptor are a start descriptor code and a descriptor type identifier code in sequence; the means for identifying the type and end of the descriptor are an end descriptor code and the descriptor type identifier code in sequence; and the means for representing the contents of the descriptor is a sequence of character codes.
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27. In the document structure of claim 26 and wherein: the means for identifying the type and start of the descriptor are a start descriptor code and a descriptor type identifier code in sequence; the means for identifying the type and end of the descriptor are an end descriptor code and the descriptor type identifier code in sequence; and the means for representing the contents of the descriptor is a sequence of character codes. 28. In the document structure of claim 27 and wherein: a start descriptor code occurring elsewhere in the document structure than at the start of a descriptor or an end descriptor code occurring elsewhere in the document structure than at the end of a descriptor is associated with an unambiguous identity code, whereby the start descriptor code or the end descriptor code is marked as not beginning or ending a descriptor.
| 0.843416 |
13. The computer program product of claim 12 , wherein storing the plurality of different object definitions in the location other than the object-oriented information model includes storing the first one of the one or more product definitions outside of the object-oriented information model.
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13. The computer program product of claim 12 , wherein storing the plurality of different object definitions in the location other than the object-oriented information model includes storing the first one of the one or more product definitions outside of the object-oriented information model. 14. The computer program product of claim 13 , wherein replacing each of the plurality of instances of the one or more objects with the reference to the one or more objects in the location other than the object-oriented information model includes replacing each instance of the first one of the one or more product definitions present in the object-oriented information model with a reference to a location where the first one of the one or more product definitions are stored outside of the object-oriented information model.
| 0.812226 |
11. A computerized system for classifying and redacting an email message for distributing to multiple recipients having different security levels, the system comprising: a processor; a non-transitory computer readable storage medium having computer readable instructions stored thereon for execution by the processor, causing the processor to: select a segment of the email message; automatically analyze contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classify the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically mark the segment in accordance with a respective classification option to produce a marked segment; automatically classify the email message based on classifications of segments of the email message; and automatically redact the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy.
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11. A computerized system for classifying and redacting an email message for distributing to multiple recipients having different security levels, the system comprising: a processor; a non-transitory computer readable storage medium having computer readable instructions stored thereon for execution by the processor, causing the processor to: select a segment of the email message; automatically analyze contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classify the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically mark the segment in accordance with a respective classification option to produce a marked segment; automatically classify the email message based on classifications of segments of the email message; and automatically redact the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. 13. The system of claim 11 , wherein the computer readable instructions further cause the processor to automatically redact the email message concurrently with writing the email message by a sender of the email message.
| 0.538505 |
21. The handheld mobile computing device of claim 17 , wherein the user interface module is further configured to receive an input from the user after generation of the annotated version of the rendering, the input indicating one or more devices to receive the annotated version of the rendering.
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21. The handheld mobile computing device of claim 17 , wherein the user interface module is further configured to receive an input from the user after generation of the annotated version of the rendering, the input indicating one or more devices to receive the annotated version of the rendering. 22. The handheld mobile computing device of claim 21 , wherein the rendering annotating module is further configured to transmit the annotated version of the rendering to a paper printer in response to the input.
| 0.936398 |
10. A method for scheduling jobs for a first processing unit device and a second processing unit device in a multi-core system, the method comprising: obtaining one or more jobs from a program, the one or more jobs configured to be executed by a plurality of threads; generating commands including asynchronous commands related to the one or more jobs in a command format including all necessary states for the command via a command processor, the generated commands being generated independently from one another on any of the plurality of threads and being executed by one or more of the plurality of threads to thereby execute the one or more jobs; translating the generated commands into a format executable by the first processing unit device and the second processing unit device; compiling data necessary for the generated commands via a data compiler into a first data format usable by a first compiler associated with a first programming language and readable by the first programming language, and a second data format usable by a second compiler associated with a second programming language and readable by the second programming language, the second programming language being distinct from the first programming language; storing the generated commands in a command buffer; assigning the generated commands to the first processing unit device, the second processing unit device, or both the first processing unit device and the second processing unit device; and storing resources for the generated commands in a transfer memory, the transfer memory being separate and distinct from the command buffer and further being accessible by the first processing unit device and the second processing unit device, the resources including program data generated by one of the first processing unit device or the second processing unit device and consumed by the other of the first processing unit device or the second processing unit device.
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10. A method for scheduling jobs for a first processing unit device and a second processing unit device in a multi-core system, the method comprising: obtaining one or more jobs from a program, the one or more jobs configured to be executed by a plurality of threads; generating commands including asynchronous commands related to the one or more jobs in a command format including all necessary states for the command via a command processor, the generated commands being generated independently from one another on any of the plurality of threads and being executed by one or more of the plurality of threads to thereby execute the one or more jobs; translating the generated commands into a format executable by the first processing unit device and the second processing unit device; compiling data necessary for the generated commands via a data compiler into a first data format usable by a first compiler associated with a first programming language and readable by the first programming language, and a second data format usable by a second compiler associated with a second programming language and readable by the second programming language, the second programming language being distinct from the first programming language; storing the generated commands in a command buffer; assigning the generated commands to the first processing unit device, the second processing unit device, or both the first processing unit device and the second processing unit device; and storing resources for the generated commands in a transfer memory, the transfer memory being separate and distinct from the command buffer and further being accessible by the first processing unit device and the second processing unit device, the resources including program data generated by one of the first processing unit device or the second processing unit device and consumed by the other of the first processing unit device or the second processing unit device. 17. The method of claim 10 , wherein the transfer memory is a graphics transfer memory.
| 0.807808 |
16. The system of claim 15 , wherein one of the data sources stores messages from artists related to the media.
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16. The system of claim 15 , wherein one of the data sources stores messages from artists related to the media. 17. The system of claim 16 , wherein the information engine obtains messages, which relate to the media, from the user's friends on the social network.
| 0.91302 |
1. A remote device for conducting a financial transaction, the remote device comprising: a mini-app dialog component selected by the customer for performing a financial transaction and providing information regarding the financial transaction to a presentation manager for presentation to the customer; a transaction executor component instantiated by the mini-app dialog component to perform the financial transaction by using at least one input, including at least an amount selected by the customer, regarding the financial transaction provided by the customer into the mini-app dialog component; and a rule broker component for receiving queries posed by the mini-app dialog component regarding the input provided by the customer to perform the financial transaction, determining a rule authority, from a plurality of rule authorities, to route the queries based on a parameter passed in the query, and routing the queries to the determined rule authority that supplies an answer to the query and defines context-specific behavior of the transaction executor component, wherein the answer is to resolve a specific inquiry regarding an unique identification contextualized for the customer using the dialog component for carrying out the financial transaction; wherein the rule authorities register themselves with the rule broker component as possible answers for particular queries, wherein the performed transaction is displayed on the remote device by the presentation manager; wherein registering to the rule broker by the rule authorities includes registering of rules provided by the respective authorities, the rules having associated parameters and constraints; wherein generating a query by the rule broker includes consulting a plurality of pre-established answers provided by a registry component internal to the rule broker; and responsive to not finding a matching answer, the rule broker applying the most suitable parameter constraints defined with one of the registered rules to formulate the query and direct it to the registered rule authority corresponding to the rule being used.
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1. A remote device for conducting a financial transaction, the remote device comprising: a mini-app dialog component selected by the customer for performing a financial transaction and providing information regarding the financial transaction to a presentation manager for presentation to the customer; a transaction executor component instantiated by the mini-app dialog component to perform the financial transaction by using at least one input, including at least an amount selected by the customer, regarding the financial transaction provided by the customer into the mini-app dialog component; and a rule broker component for receiving queries posed by the mini-app dialog component regarding the input provided by the customer to perform the financial transaction, determining a rule authority, from a plurality of rule authorities, to route the queries based on a parameter passed in the query, and routing the queries to the determined rule authority that supplies an answer to the query and defines context-specific behavior of the transaction executor component, wherein the answer is to resolve a specific inquiry regarding an unique identification contextualized for the customer using the dialog component for carrying out the financial transaction; wherein the rule authorities register themselves with the rule broker component as possible answers for particular queries, wherein the performed transaction is displayed on the remote device by the presentation manager; wherein registering to the rule broker by the rule authorities includes registering of rules provided by the respective authorities, the rules having associated parameters and constraints; wherein generating a query by the rule broker includes consulting a plurality of pre-established answers provided by a registry component internal to the rule broker; and responsive to not finding a matching answer, the rule broker applying the most suitable parameter constraints defined with one of the registered rules to formulate the query and direct it to the registered rule authority corresponding to the rule being used. 13. The system of claim 1 , wherein the rule broker component directs a querying component to a rule authority for the answer to the question.
| 0.579278 |
1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values.
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1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values. 9. The method of claim 1 wherein the hierarchical data structure is a binary trie.
| 0.651316 |
1. A method comprising: accessing seed metadata, the seed metadata describing a seed, the seed being a basis on which a station library is to be defined; generating a station descriptor profile based on the seed metadata, the station descriptor profile defining a genre composition of the station library; generating a candidate set based on the seed metadata, the candidate set comprising a plurality of candidate media files; for each candidate media file in the candidate set: computing a similarity score associated with the candidate media file, the similarity score including a measure of similarity between the candidate media file and the station descriptor profile; computing one or more boost values associated with the candidate media file based on candidate metadata describing the candidate media file; and computing a relevancy score associated with the candidate media file based on the similarity score and the one or more boost values associated with the candidate media file, the relevancy score providing a basis for selecting the candidate media file for inclusion in the station library; and machine-generating a station set including a portion of the candidate set selected based on the relevancy scores associated with the plurality of candidate media files included in the candidate set, the machine-generated station set defining the station library by referencing each candidate media file in the portion of the candidate set, wherein the station descriptor profile includes one or more focus genre profiles and each candidate media file includes a file genre profile, the one or more focus genre profiles and the file genre profile each including respective multiple genre values and a weight assigned to each genre value, each genre value corresponding to a genre, each weight indicating a percentage of the corresponding genre value relative to the other genre values in the respective multiple genre values, and computing the similarity score associated with the candidate media file includes: computing one or more focus-level similarity scores by comparing, for each focus genre profile in the station descriptor profile: (a) the respective multiple genre values and the corresponding weights of the focus genre profile, and (b) the respective multiple genre values and the corresponding weights of the file genre profile of the candidate media file; and selecting the highest focus-level similarity score to be the similarity score associated with the candidate media file.
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1. A method comprising: accessing seed metadata, the seed metadata describing a seed, the seed being a basis on which a station library is to be defined; generating a station descriptor profile based on the seed metadata, the station descriptor profile defining a genre composition of the station library; generating a candidate set based on the seed metadata, the candidate set comprising a plurality of candidate media files; for each candidate media file in the candidate set: computing a similarity score associated with the candidate media file, the similarity score including a measure of similarity between the candidate media file and the station descriptor profile; computing one or more boost values associated with the candidate media file based on candidate metadata describing the candidate media file; and computing a relevancy score associated with the candidate media file based on the similarity score and the one or more boost values associated with the candidate media file, the relevancy score providing a basis for selecting the candidate media file for inclusion in the station library; and machine-generating a station set including a portion of the candidate set selected based on the relevancy scores associated with the plurality of candidate media files included in the candidate set, the machine-generated station set defining the station library by referencing each candidate media file in the portion of the candidate set, wherein the station descriptor profile includes one or more focus genre profiles and each candidate media file includes a file genre profile, the one or more focus genre profiles and the file genre profile each including respective multiple genre values and a weight assigned to each genre value, each genre value corresponding to a genre, each weight indicating a percentage of the corresponding genre value relative to the other genre values in the respective multiple genre values, and computing the similarity score associated with the candidate media file includes: computing one or more focus-level similarity scores by comparing, for each focus genre profile in the station descriptor profile: (a) the respective multiple genre values and the corresponding weights of the focus genre profile, and (b) the respective multiple genre values and the corresponding weights of the file genre profile of the candidate media file; and selecting the highest focus-level similarity score to be the similarity score associated with the candidate media file. 7. The method of claim 1 , wherein: the computing of the one or more boost values includes computing a recency artist boost value associated with the candidate media file based on a temporal value attribute associated with the seed in combination with a temporal attribute of the candidate media file included in candidate metadata describing the candidate media file.
| 0.507249 |
14. The information processing device according to claim 12 , wherein one or more processors are configured to: extract words included in the text of the caption displayed in a window as one document while shifting the window of a predetermined time length at regular intervals; extract a frequency of appearance of each word in the document as the text feature amount; obtain a parameter of LDA (latent Dirichlet allocation) as the basis space data of the basis space for text by learning the LDA by using the document obtained from the learning content; and convert the text feature amount obtained from the document to topic likelihood, which is likelihood of each latent topic of the LDA for the document to obtain a topic label representing the latent topic for which topic likelihood is maximum after the dimension reduction.
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14. The information processing device according to claim 12 , wherein one or more processors are configured to: extract words included in the text of the caption displayed in a window as one document while shifting the window of a predetermined time length at regular intervals; extract a frequency of appearance of each word in the document as the text feature amount; obtain a parameter of LDA (latent Dirichlet allocation) as the basis space data of the basis space for text by learning the LDA by using the document obtained from the learning content; and convert the text feature amount obtained from the document to topic likelihood, which is likelihood of each latent topic of the LDA for the document to obtain a topic label representing the latent topic for which topic likelihood is maximum after the dimension reduction. 16. The information processing device according to claim 14 , wherein the one or more processors are configured to: search a keyword frame from target content from which the keyword frame, which is a frame with a predetermined keyword, is to be searched by using the annotation model; generate a word dictionary of the words appearing in the document by using the document obtained from the learning content; create a topic-to-frequently appearing word table of each word with an appearance frequency greater than or equal to a predetermined threshold in the latent topic of the LDA and the corresponding appearance frequency by using occurrence probability of each word in the word dictionary in each latent topic of the LDA; extract the image feature amount of each frame of the image of the target content; perform the dimension reduction; compose the annotation sequence by using the image feature amount after the dimension reduction; obtain a maximum likelihood state sequence in which the annotation sequence is observed in the annotation model; select the latent topic represented by the topic label with the maximum topic likelihood in a state corresponding to a target frame out of states of the maximum likelihood state sequence as a frame topic representing a content of the target frame; obtain an appearance frequency of the predetermined keyword in the frame topic based on the topic-to-frequently appearing word table; and select, when the appearance frequency of the predetermined keyword is greater than or equal to the predetermined threshold, the target frame as the keyword frame.
| 0.501989 |
5. A program storage device readable by a computer system, tangibly embodying a program of instructions executable by one or more processors of the computer system to perform method steps for aggregating information from multiple data sources, said method steps comprising: receiving information regarding a user selection event identifying a plurality of taxonomy objects to be imported into the reporting/analysis application; responsive to the user selection event, retrieving business data corresponding to the plurality of taxonomy objects from a plurality of data sources, including a first data source containing financial reporting (FR) level information and a second data source containing general ledger (GL) level information; and generating and displaying an aggregated result within a single cell of a spreadsheet representing a combination of at least a portion of business data retrieved from the first data source and a portion of business data retrieved from the second data source.
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5. A program storage device readable by a computer system, tangibly embodying a program of instructions executable by one or more processors of the computer system to perform method steps for aggregating information from multiple data sources, said method steps comprising: receiving information regarding a user selection event identifying a plurality of taxonomy objects to be imported into the reporting/analysis application; responsive to the user selection event, retrieving business data corresponding to the plurality of taxonomy objects from a plurality of data sources, including a first data source containing financial reporting (FR) level information and a second data source containing general ledger (GL) level information; and generating and displaying an aggregated result within a single cell of a spreadsheet representing a combination of at least a portion of business data retrieved from the first data source and a portion of business data retrieved from the second data source. 8. The program storage device of claim 5 , further comprising storing a summary of the business data in an XBRL document.
| 0.872917 |
20. A non-transitory computer readable storage medium for tangibly storing thereon computer readable instructions for a method comprising: receiving, at a computing device, activity history associated with a user from a network data source, the activity history comprising a description of a user action initiated by the user; generating, by the computing device, a first metadata item based upon the activity history; storing, by the computing device, the first metadata item as user profile information associated with the user in a user profile database in response to a number of times the first metadata item is generated in a defined time period being greater than a threshold value; providing, by the computing device, a link to a widget plugin for inclusion with content objects of a content server that is disparate from the computing device and the network data source, the widget plugin enables communication between the computing device and a client computer associated with the user, the widget plugin enables via the communication, scanning of content objects received by the client computer and automatic retrieval of a subset of the content objects relevant to the first metadata item; receiving, by the computing device, a request for user-related metadata relevant to the content objects of provided by the content server to the client computer in response to navigation of the user to a website of the content server; determining, by the computing device, that the first metadata item is relevant to the content objects; transmitting, by the computing device, the first metadata item to an entity that made the request; enabling, by the computing device via the provision of the widget plugin link, automatic retrieval of a subset of the content objects that are relevant to the first metadata item for display to the user; and removing, by the computing device, the first metadata item from the user profile database in response to a number of times the first metadata item is generated in a defined time period being less than the threshold value.
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20. A non-transitory computer readable storage medium for tangibly storing thereon computer readable instructions for a method comprising: receiving, at a computing device, activity history associated with a user from a network data source, the activity history comprising a description of a user action initiated by the user; generating, by the computing device, a first metadata item based upon the activity history; storing, by the computing device, the first metadata item as user profile information associated with the user in a user profile database in response to a number of times the first metadata item is generated in a defined time period being greater than a threshold value; providing, by the computing device, a link to a widget plugin for inclusion with content objects of a content server that is disparate from the computing device and the network data source, the widget plugin enables communication between the computing device and a client computer associated with the user, the widget plugin enables via the communication, scanning of content objects received by the client computer and automatic retrieval of a subset of the content objects relevant to the first metadata item; receiving, by the computing device, a request for user-related metadata relevant to the content objects of provided by the content server to the client computer in response to navigation of the user to a website of the content server; determining, by the computing device, that the first metadata item is relevant to the content objects; transmitting, by the computing device, the first metadata item to an entity that made the request; enabling, by the computing device via the provision of the widget plugin link, automatic retrieval of a subset of the content objects that are relevant to the first metadata item for display to the user; and removing, by the computing device, the first metadata item from the user profile database in response to a number of times the first metadata item is generated in a defined time period being less than the threshold value. 27. The non-transitory computer readable storage medium of claim 20 , wherein the activity history comprises a description of a user action in which the user creates online content, provides online content to the network data source, shares a web link with another user, applies a tag to another user, receives online content, or a combination thereof.
| 0.5 |
10. A method for use with a given patent having a claim set of one or more claims, said given patent having an identifier and a reference date, the method comprising: building a dictionary of terms for a group of patents, each of the patents having an identifier, a reference date, and a claim set of one or more claims, wherein each of the terms occurs in the claim set of at least one of the patents; identifying for each term a date of first usage corresponding to the earliest reference date among patents in the group having a claim set in which that term is used; identifying, within the claim set of said given patent, at least one particular term that is in the dictionary; and using a computer to evaluate said particular term in said given patent by determining the time difference between: a) the reference date of said given patent, and b) the date of first usage for said particular term.
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10. A method for use with a given patent having a claim set of one or more claims, said given patent having an identifier and a reference date, the method comprising: building a dictionary of terms for a group of patents, each of the patents having an identifier, a reference date, and a claim set of one or more claims, wherein each of the terms occurs in the claim set of at least one of the patents; identifying for each term a date of first usage corresponding to the earliest reference date among patents in the group having a claim set in which that term is used; identifying, within the claim set of said given patent, at least one particular term that is in the dictionary; and using a computer to evaluate said particular term in said given patent by determining the time difference between: a) the reference date of said given patent, and b) the date of first usage for said particular term. 13. The method of claim 10 , further comprising: repeating said evaluating step for at least one additional term occurring in said given patent's claim set.
| 0.657316 |
1. A system including instructions stored on a non-transitory computer-readable medium and executable by at least one processor of one or more computing devices, the system comprising: a Web Service Description Language (WSDL) inspector configured to cause the at least one processor to: discover, using a registry of discoverable web services, an existing web service that provides web service functionality; receive a WSDL file describing the web service, loop over all data type definitions in order to determine at least one data type included in the WSDL file, create and store a proxy data type corresponding to the at least one data type which is available to a business object generator, and extract at least one interface operation from the WSDL file, the at least one interface operation including at least one message sent during implementation of the at least one interface operation, the at least one message using the at least one data type; and the business object generator is configured to cause the at least one processor to: generate a business object based on the WSDL file, the business object including the at least one data type and the at least one interface operation, the business object configured to expose the web service functionality in an integrated manner within a business object based application environment, the generating including: converting the at least one data type to a format consistent with the business object based application environment, creating at least one business object node of the business object that corresponds to each interface operation of the WSDL file, the at least one business object node being based on the at least one message, and creating a node action for the at least one business object node, the node action corresponding to the at least one interface operation.
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1. A system including instructions stored on a non-transitory computer-readable medium and executable by at least one processor of one or more computing devices, the system comprising: a Web Service Description Language (WSDL) inspector configured to cause the at least one processor to: discover, using a registry of discoverable web services, an existing web service that provides web service functionality; receive a WSDL file describing the web service, loop over all data type definitions in order to determine at least one data type included in the WSDL file, create and store a proxy data type corresponding to the at least one data type which is available to a business object generator, and extract at least one interface operation from the WSDL file, the at least one interface operation including at least one message sent during implementation of the at least one interface operation, the at least one message using the at least one data type; and the business object generator is configured to cause the at least one processor to: generate a business object based on the WSDL file, the business object including the at least one data type and the at least one interface operation, the business object configured to expose the web service functionality in an integrated manner within a business object based application environment, the generating including: converting the at least one data type to a format consistent with the business object based application environment, creating at least one business object node of the business object that corresponds to each interface operation of the WSDL file, the at least one business object node being based on the at least one message, and creating a node action for the at least one business object node, the node action corresponding to the at least one interface operation. 5. The system of claim 1 wherein one or more node service operations correspond to the at least one interface operation.
| 0.552817 |
1. A method for determining a pupillary response to a multimedia data element (MMDE) viewed through a user computing device, comprising: receiving a first image of a viewer's pupil captured prior to display of the MMDE over the user computing device; receiving a second image of a viewer's pupil captured after the display of the MMDE over the user computing device; determining, using the first image and the second image, if the viewer's pupil has been dilated; when identifying of a pupil dilation, querying a deep-content-classification (DCC) system to find a match between at least one concept structure and the at least second image of the user's pupil; upon identification of at least one matching concept, receiving a first set of metadata related to the at least one matching concept structure; determining the viewer's attention to the displayed MMDE respective of the first set of metadata; and associating the at least one MMDE with the determined user attention.
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1. A method for determining a pupillary response to a multimedia data element (MMDE) viewed through a user computing device, comprising: receiving a first image of a viewer's pupil captured prior to display of the MMDE over the user computing device; receiving a second image of a viewer's pupil captured after the display of the MMDE over the user computing device; determining, using the first image and the second image, if the viewer's pupil has been dilated; when identifying of a pupil dilation, querying a deep-content-classification (DCC) system to find a match between at least one concept structure and the at least second image of the user's pupil; upon identification of at least one matching concept, receiving a first set of metadata related to the at least one matching concept structure; determining the viewer's attention to the displayed MMDE respective of the first set of metadata; and associating the at least one MMDE with the determined user attention. 9. The method of claim 1 , wherein a concept structure is a signature reduced cluster of signatures describing multimedia elements.
| 0.754484 |
19. The system of claim 15 , wherein the instructions further include instructions to: identify a second user, wherein the second user is in a grouping with the user but has not consumed the provided media file; identify a second search query entered by the second user; identify a plurality of second query suggestions, wherein the plurality of second query suggestions are responsive to the second search query; and select one or more of the plurality of second query suggestions to provide to the second user, wherein a likelihood of a given second query suggestion being provided to the second user is determined based at least in part on a similarity between the given second query suggestion and the aspect and is determined based on identifying the association of the user to the provided media file and the second user being in the grouping with the user.
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19. The system of claim 15 , wherein the instructions further include instructions to: identify a second user, wherein the second user is in a grouping with the user but has not consumed the provided media file; identify a second search query entered by the second user; identify a plurality of second query suggestions, wherein the plurality of second query suggestions are responsive to the second search query; and select one or more of the plurality of second query suggestions to provide to the second user, wherein a likelihood of a given second query suggestion being provided to the second user is determined based at least in part on a similarity between the given second query suggestion and the aspect and is determined based on identifying the association of the user to the provided media file and the second user being in the grouping with the user. 20. The system of claim 19 , wherein the provided media file is shared by the user with the second user.
| 0.80107 |
15. The computer program product of claim 11 , further comprising generating first barcode stamps which encode the processed data generated in step (b); wherein step (e) further includes printing the first barcode stamps on a front or back side of the same recording medium to generate the printed document.
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15. The computer program product of claim 11 , further comprising generating first barcode stamps which encode the processed data generated in step (b); wherein step (e) further includes printing the first barcode stamps on a front or back side of the same recording medium to generate the printed document. 16. The computer program product of claim 15 , wherein the first barcode further encodes metadata relating to the printed document, and wherein in step (d) the hierarchical barcode stamp further encodes the metadata.
| 0.888016 |
10. A speech for recognizing speech, comprising: a microphone configured to receive an utterance from a source, the utterance potentially containing a particular expression, wherein the particular expression is capable of being associated with at least two different meanings; a processor selectively and operatively connected to the microphone, the processor including: computer readable code for determining that the utterance contains the particular expression; computer readable code for splitting the utterance into a plurality of speech frames, each frame being assigned a predetermined time segment and a frame number; and computer readable code for indexing the utterance to i) a predetermined frame number, or ii) a predetermined time segment, the indexing identifying that one of the plurality of frames includes the particular expression; and means for re-presenting the one of the plurality of frames including the particular expression to the speech recognition system to verify that the particular expression was actually recited in the utterance.
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10. A speech for recognizing speech, comprising: a microphone configured to receive an utterance from a source, the utterance potentially containing a particular expression, wherein the particular expression is capable of being associated with at least two different meanings; a processor selectively and operatively connected to the microphone, the processor including: computer readable code for determining that the utterance contains the particular expression; computer readable code for splitting the utterance into a plurality of speech frames, each frame being assigned a predetermined time segment and a frame number; and computer readable code for indexing the utterance to i) a predetermined frame number, or ii) a predetermined time segment, the indexing identifying that one of the plurality of frames includes the particular expression; and means for re-presenting the one of the plurality of frames including the particular expression to the speech recognition system to verify that the particular expression was actually recited in the utterance. 11. The system as defined in claim 10 wherein the processor further includes: computer readable code for generating an N-best list for the utterance, the N-best list including a plurality of possible utterances, each of which potentially corresponds with the utterance, wherein each of the plurality of possible utterances is ranked according to a confidence score; and computer readable code for identifying a first-best possible utterance from the N-best list, the first-best possible utterance being ranked the highest among the plurality of possible utterances according to its confidence score, wherein the first-best possible utterance contains one meaning of the particular expression.
| 0.5 |
15. A computer storage device comprising instructions that when executed perform a method, comprising: matching a first target term, comprised in a target string, to a first known term in an index tree, the first known term associated with a known string identifier (ID); matching a second target term, comprised in the target string, to a second known term in the index tree, the second known term associated with the known string ID; and responsive to determining that a threshold number of target terms, comprising the first target term and the second target term, comprised in the target string are respectively matched with a known term associated with the known string ID, matching the target string to a known string associated with the known string ID.
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15. A computer storage device comprising instructions that when executed perform a method, comprising: matching a first target term, comprised in a target string, to a first known term in an index tree, the first known term associated with a known string identifier (ID); matching a second target term, comprised in the target string, to a second known term in the index tree, the second known term associated with the known string ID; and responsive to determining that a threshold number of target terms, comprising the first target term and the second target term, comprised in the target string are respectively matched with a known term associated with the known string ID, matching the target string to a known string associated with the known string ID. 16. The computer storage device of claim 15 , the first target term different than the second target term.
| 0.627273 |
25. The system of claim 17 , wherein one or more of nodes comprise any of mobile phones, personal digital assistants, network-enabled digital picture frames, personal computers, and third-party servers.
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25. The system of claim 17 , wherein one or more of nodes comprise any of mobile phones, personal digital assistants, network-enabled digital picture frames, personal computers, and third-party servers. 26. The system of claim 25 , wherein one or more of the third-party servers comprises any of a photo-sharing web site, a digital media company, and/or other repository of content.
| 0.949119 |
1. A method for generating, maintaining, updating, and augmenting a working database containing documents used as references for other documents in said working database, said method executed as a supplemental program operable within a word processor, said method comprising the steps of: searching a new document for symbols, retrieving said symbols and replacing said retrieved symbols with text representing said retrieved symbols; searching said new document for images, retrieving said images and replacing said retrieved images with text representing said retrieved images; parsing all text within said new document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually moving said markers within said new document, said movement of said markers accomplished by a user manually adjusting said markers to user specified positions within said new document; deleting said markers within said new document by said user manually deleting said markers; adding additional markers within said new document by said user manually inserting said additional markers to user specified positions within said new document; highlighting marked discrete clusters within said new document for verification by said user; assigning one or more identification codes corresponding one or more said marked discrete clusters within said new document; uploading said new document into said working database; verifying the upload of said new document into a file system of said working database by providing a file name and location of said new document within said file system; searching said working database for text, including general text, said text representing retrieved symbols, and said text representing retrieved images by querying said working database using a search string, said document file name, said document location, and or said identification code representing a discrete cluster; retrieving one or more relevant parent documents from said working database, said parent documents containing said text relevant to said search; generating a child document by said user selecting text from one or more discrete clusters within one or more of said relevant parent documents; inserting said selected text into said child document, said insertion allowing elective retention of parent document identification codes within said inserted text in said child document; searching said child document for symbols and images, replacing said symbols and said images with text representing said retrieved symbols and images; manually augmenting said inserted text and within said child document, said augmentation allowing addition to, removal, and/or alteration of said inserted text within said child document, said manual augmentation allowing paraphrasing of said inserted text, parsing all text within said child document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually adjusting said markers around said paraphrasing in said child document, while maintaining matches between the said discrete clusters in said parent documents and said discrete clusters in said child documents; assigning identification codes to said inserted text within said discrete clusters within said child document; automatically generating links between said inserted text within said child document to said selected text within one or more of said parent documents corresponding to said inserted text, said links containing said parent document identification codes retained within said inserted text and said child document identification codes; automatically generating links between said inserted text within said child document and said selected text within one or more of said parent documents corresponding to said inserted text by searching said working database for parent documents containing matches to said inserted text within said discrete clusters of said child documents, said links containing said parent document identification codes and said child document identification codes; manually generating links between said inserted text within said child document and said selected text within one or more said discrete clusters with said parent documents, said links containing said parent document identification codes and said child document identification codes; maintaining a registry of said links in said working database, said registry prompting child document authors when one or more of said parent documents are augmented, said prompting giving notice of said augmentation of said parent document; automatically generating citations for said inserted text within said child document using said links, said automatically generated citations referencing corresponding discrete clusters within said parent documents, said citations generated in a pre-set format, customizable by said user; inserting said citations into said child document, said citations being movable or augmentable by said user; uploading said child document into said working database while allowing said user to electively remove said parent document identification codes within said child document prior to uploading; verifying said upload of said child document into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; searching said working database for exact matches between the text of said child document and text of all documents stored within said working database and searching said working database for exact matches to said parent document identification codes retained within said child document, if said exact matches are retrieved, said method includes updating positioning of said markers within said child document corresponding to said discrete clusters within said exact matches; prompting said user when said exact matches are not retrieved and providing a list of best matches between said text of said child document and said discrete clusters of documents stored within said working database, said user selecting a best match which reposition said markers in said child document corresponding to the text of said best match; uploading said child document containing said new markers; verifying said upload of said child document containing said new markers into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; tracking modifications to text, symbols, format, and/or images of said documents within said working database; alerting said user when said modifications occur; comparing said documents within said working database by aligning one or more referenced documents with one or more referencing documents and tagging the differences between said documents.
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1. A method for generating, maintaining, updating, and augmenting a working database containing documents used as references for other documents in said working database, said method executed as a supplemental program operable within a word processor, said method comprising the steps of: searching a new document for symbols, retrieving said symbols and replacing said retrieved symbols with text representing said retrieved symbols; searching said new document for images, retrieving said images and replacing said retrieved images with text representing said retrieved images; parsing all text within said new document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually moving said markers within said new document, said movement of said markers accomplished by a user manually adjusting said markers to user specified positions within said new document; deleting said markers within said new document by said user manually deleting said markers; adding additional markers within said new document by said user manually inserting said additional markers to user specified positions within said new document; highlighting marked discrete clusters within said new document for verification by said user; assigning one or more identification codes corresponding one or more said marked discrete clusters within said new document; uploading said new document into said working database; verifying the upload of said new document into a file system of said working database by providing a file name and location of said new document within said file system; searching said working database for text, including general text, said text representing retrieved symbols, and said text representing retrieved images by querying said working database using a search string, said document file name, said document location, and or said identification code representing a discrete cluster; retrieving one or more relevant parent documents from said working database, said parent documents containing said text relevant to said search; generating a child document by said user selecting text from one or more discrete clusters within one or more of said relevant parent documents; inserting said selected text into said child document, said insertion allowing elective retention of parent document identification codes within said inserted text in said child document; searching said child document for symbols and images, replacing said symbols and said images with text representing said retrieved symbols and images; manually augmenting said inserted text and within said child document, said augmentation allowing addition to, removal, and/or alteration of said inserted text within said child document, said manual augmentation allowing paraphrasing of said inserted text, parsing all text within said child document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually adjusting said markers around said paraphrasing in said child document, while maintaining matches between the said discrete clusters in said parent documents and said discrete clusters in said child documents; assigning identification codes to said inserted text within said discrete clusters within said child document; automatically generating links between said inserted text within said child document to said selected text within one or more of said parent documents corresponding to said inserted text, said links containing said parent document identification codes retained within said inserted text and said child document identification codes; automatically generating links between said inserted text within said child document and said selected text within one or more of said parent documents corresponding to said inserted text by searching said working database for parent documents containing matches to said inserted text within said discrete clusters of said child documents, said links containing said parent document identification codes and said child document identification codes; manually generating links between said inserted text within said child document and said selected text within one or more said discrete clusters with said parent documents, said links containing said parent document identification codes and said child document identification codes; maintaining a registry of said links in said working database, said registry prompting child document authors when one or more of said parent documents are augmented, said prompting giving notice of said augmentation of said parent document; automatically generating citations for said inserted text within said child document using said links, said automatically generated citations referencing corresponding discrete clusters within said parent documents, said citations generated in a pre-set format, customizable by said user; inserting said citations into said child document, said citations being movable or augmentable by said user; uploading said child document into said working database while allowing said user to electively remove said parent document identification codes within said child document prior to uploading; verifying said upload of said child document into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; searching said working database for exact matches between the text of said child document and text of all documents stored within said working database and searching said working database for exact matches to said parent document identification codes retained within said child document, if said exact matches are retrieved, said method includes updating positioning of said markers within said child document corresponding to said discrete clusters within said exact matches; prompting said user when said exact matches are not retrieved and providing a list of best matches between said text of said child document and said discrete clusters of documents stored within said working database, said user selecting a best match which reposition said markers in said child document corresponding to the text of said best match; uploading said child document containing said new markers; verifying said upload of said child document containing said new markers into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; tracking modifications to text, symbols, format, and/or images of said documents within said working database; alerting said user when said modifications occur; comparing said documents within said working database by aligning one or more referenced documents with one or more referencing documents and tagging the differences between said documents. 7. The system of claim 1 , in which said parent documents may also be a child document to other parent documents.
| 0.928212 |
10. The communication system of claim 9 , further comprising a translator module coupled with said automatic speech recognizer and said speech output device, said translator configured to convert said text sequence from a first language to a second language.
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10. The communication system of claim 9 , further comprising a translator module coupled with said automatic speech recognizer and said speech output device, said translator configured to convert said text sequence from a first language to a second language. 15. The communication system of claim 10 , wherein said translator module includes a plurality of translator modules.
| 0.914363 |
10. One or more processor readable storage devices according to claim 9 , wherein said step of generating a threat model includes: receiving input associated with prioritizing a generated threat.
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10. One or more processor readable storage devices according to claim 9 , wherein said step of generating a threat model includes: receiving input associated with prioritizing a generated threat. 11. One or more processor readable storage devices according to claim 10 , wherein said step of prioritizing includes: prioritizing the impact or probability associated with the generated threat.
| 0.929749 |
1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer.
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1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer. 2. A method according to claim 1 wherein a tv camera is used to make said electro-optical determination.
| 0.625 |
1. A method, implemented by one or more computing devices, for processing linguistic items, comprising: receiving a word sequence formed by a sequence of words; forming a plurality of window vectors, each representing a set of z consecutive words in the word sequence; transforming the window vectors into a plurality of local contextual feature (LCF) vectors, based on a first part of a convolutional latent semantic model; generating a global feature vector by selecting, for each dimension of the LCF vectors, a maximum value specified by the LCF vectors, with respect to that dimension; and projecting the global feature vector into a concept vector, based on a second part of the convolutional latent semantic model, the convolutional latent semantic model being trained based on click-through data.
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1. A method, implemented by one or more computing devices, for processing linguistic items, comprising: receiving a word sequence formed by a sequence of words; forming a plurality of window vectors, each representing a set of z consecutive words in the word sequence; transforming the window vectors into a plurality of local contextual feature (LCF) vectors, based on a first part of a convolutional latent semantic model; generating a global feature vector by selecting, for each dimension of the LCF vectors, a maximum value specified by the LCF vectors, with respect to that dimension; and projecting the global feature vector into a concept vector, based on a second part of the convolutional latent semantic model, the convolutional latent semantic model being trained based on click-through data. 9. The method of claim 1 , wherein the convolutional latent semantic model is produced in a training process by maximizing a conditional likelihood of clicked documents, or keywords associated with clicked ads, given specified queries.
| 0.671823 |
1. A method of implementing setup configurations for a network interface device, comprising: identifying a plurality of electronic parameters that need to be programmed into memory associated with a network interface device to properly establish a communication link with at least one other node in a communication network; electronically providing a graphical user interface to a user, said graphical user interface comprising a plurality of interface elements configured to receive data defining a first set of variable parameters, wherein said first set of variable parameters corresponds to variable parameters which change based on at least one of user selection and customization, at least one of said user selection and customization being based upon specific options available to a client of said network interface device; analyzing and mapping the first set of variable parameters to a set of static parameters electronically via an application layer module, wherein said set of static parameters corresponds to static parameters required to program said network interface device, said static parameters being defined at least in part by direct dependencies with data which defines the first set of variable parameters; electronically receiving from a user data defining the first set of variable parameters as provided via the graphical user interface; electronically accessing a data file defining the set of static parameters; automatically programming the memory associated with the network interface device to establish a communication link in accordance with a configuration defined by the first set of variable parameters provided via the graphical user interface and the set of static parameters electronically accessed by the data file.
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1. A method of implementing setup configurations for a network interface device, comprising: identifying a plurality of electronic parameters that need to be programmed into memory associated with a network interface device to properly establish a communication link with at least one other node in a communication network; electronically providing a graphical user interface to a user, said graphical user interface comprising a plurality of interface elements configured to receive data defining a first set of variable parameters, wherein said first set of variable parameters corresponds to variable parameters which change based on at least one of user selection and customization, at least one of said user selection and customization being based upon specific options available to a client of said network interface device; analyzing and mapping the first set of variable parameters to a set of static parameters electronically via an application layer module, wherein said set of static parameters corresponds to static parameters required to program said network interface device, said static parameters being defined at least in part by direct dependencies with data which defines the first set of variable parameters; electronically receiving from a user data defining the first set of variable parameters as provided via the graphical user interface; electronically accessing a data file defining the set of static parameters; automatically programming the memory associated with the network interface device to establish a communication link in accordance with a configuration defined by the first set of variable parameters provided via the graphical user interface and the set of static parameters electronically accessed by the data file. 8. The method of claim 1 , wherein said first set of variable parameters comprises a file pointer for a data file defining all data identified by the second set of static parameters as well as any additional parameters other than the file pointer in the first set of variable parameters, and wherein said method further comprises a step of programming the memory associated with the network interface device with the data file.
| 0.627386 |
12. The method of claim 1 , wherein providing an indicator that the search item result is associated with malware comprises at least one of: transmitting the indicator to a client device component; transmitting the indicator to a gateway; and transmitting the indicator to a firewall.
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12. The method of claim 1 , wherein providing an indicator that the search item result is associated with malware comprises at least one of: transmitting the indicator to a client device component; transmitting the indicator to a gateway; and transmitting the indicator to a firewall. 13. The method of claim 12 , wherein the client device component comprises a browser component designed to perform one or more of: denying access to a search item result network site indicated as associated with malware; providing a warning about a search item result network site indicated as associated with malware; and activating one or more security components to reduce a threat from a search item result network site indicated as associated with malware.
| 0.63173 |
1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a subgraph of a multi-partite graph, wherein the received subgraph encompasses search queries; receiving a global center vector table that includes cluster center entries for query clusters; filtering the received global center vector table to eliminate one or more cluster center entries that are irrelevant to the search queries in the received subgraph; and clustering the search queries in the received subgraph into the query clusters by at least comparing each of the search queries to at least some of the cluster center entries in the received global center vector table, wherein the clustering includes eliminating a comparison between a cluster center entry in the received global center vector table and a search query of the search queries by using a user-centered table that lists related cluster centers for each user enumerated in the received global center vector table and a URL-centered table that lists related cluster centers for each URL enumerated in the received global center vector table.
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1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a subgraph of a multi-partite graph, wherein the received subgraph encompasses search queries; receiving a global center vector table that includes cluster center entries for query clusters; filtering the received global center vector table to eliminate one or more cluster center entries that are irrelevant to the search queries in the received subgraph; and clustering the search queries in the received subgraph into the query clusters by at least comparing each of the search queries to at least some of the cluster center entries in the received global center vector table, wherein the clustering includes eliminating a comparison between a cluster center entry in the received global center vector table and a search query of the search queries by using a user-centered table that lists related cluster centers for each user enumerated in the received global center vector table and a URL-centered table that lists related cluster centers for each URL enumerated in the received global center vector table. 2. The computer-readable medium of claim 1 , further comprising instructions that, when executed, cause the one or more processors to perform an act of updating the global center vector table with a new cluster center entry or at least one feature vector for an existing cluster center entry to generate an updated global center vector table.
| 0.610563 |
14. The computer program product of claim 10 , wherein said generating the target language HTTP request comprises: determining from the globalization rules: the respective target parameter string corresponding to each host parameter string of the at least one host parameter string in the host language HTTP request; and replacing each host parameter string of the at least one host parameter string in the host language HTTP request with the respective target parameter string determined from the globalization rules.
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14. The computer program product of claim 10 , wherein said generating the target language HTTP request comprises: determining from the globalization rules: the respective target parameter string corresponding to each host parameter string of the at least one host parameter string in the host language HTTP request; and replacing each host parameter string of the at least one host parameter string in the host language HTTP request with the respective target parameter string determined from the globalization rules. 16. The computer program product of claim 14 , wherein a date format parameter string of the at least one host parameter string in the host language HTTP request specifies a format for a month, day, and year of a date.
| 0.892127 |
16. Computer readable apparatus comprising a storage medium, said storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to, based on at least first information relating to a first location and second information relating to a second location, the first and second locations being part of a common journey: identify a first entity associated with the first location; identify a second entity associated with the second location; present first advertising content related to the first entity; and present second advertising content related to the second entity.
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16. Computer readable apparatus comprising a storage medium, said storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to, based on at least first information relating to a first location and second information relating to a second location, the first and second locations being part of a common journey: identify a first entity associated with the first location; identify a second entity associated with the second location; present first advertising content related to the first entity; and present second advertising content related to the second entity. 19. The apparatus of claim 16 , wherein the first advertising content and the second advertising content are selected based at least in part on the respective available presentation times before the first location and second location are to be encountered during said journey.
| 0.758895 |
5. A non-transitory computer readable media encoded with instructions that are operable, when executed by one or more computers, to cause the one or more computers to perform operations comprising: retrieving, by an information retrieval system comprising one or more computers, a group of documents over a network, each document in the group of documents being located at a respective network location; identifying links occurring in the group of documents, wherein each link occurring in the group of documents has associated anchor text and points to a network location of another document in the group of documents; translating, by one or more translation engines installed on one or more computers of the information retrieval system, each document in the group of documents into each of a plurality of target languages using a respective context-specific translation model for each of the target languages to generate a respective translated document in each target language for each of the documents in the group, wherein the context of each respective context-specific translation model depends at least in part on the anchor text of one or more of the identified links pointing to the document; translating, by one or more translation engines, into each of the target languages the anchor text of the links pointing to documents in the group to generate translated anchor texts; indexing the translated anchor texts; indexing the documents in the group and the translated documents; receiving, over the network by a search engine installed on the one or more computers of the information retrieval system, a query in a first language, the first language being one of the target languages, after the translating and indexing of the documents and the anchor texts; and searching, by the search engine, the documents in the group that are in the first language, the translated documents that are in the first language, and the translated anchor texts that are in the first language to identify documents responsive to the query.
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5. A non-transitory computer readable media encoded with instructions that are operable, when executed by one or more computers, to cause the one or more computers to perform operations comprising: retrieving, by an information retrieval system comprising one or more computers, a group of documents over a network, each document in the group of documents being located at a respective network location; identifying links occurring in the group of documents, wherein each link occurring in the group of documents has associated anchor text and points to a network location of another document in the group of documents; translating, by one or more translation engines installed on one or more computers of the information retrieval system, each document in the group of documents into each of a plurality of target languages using a respective context-specific translation model for each of the target languages to generate a respective translated document in each target language for each of the documents in the group, wherein the context of each respective context-specific translation model depends at least in part on the anchor text of one or more of the identified links pointing to the document; translating, by one or more translation engines, into each of the target languages the anchor text of the links pointing to documents in the group to generate translated anchor texts; indexing the translated anchor texts; indexing the documents in the group and the translated documents; receiving, over the network by a search engine installed on the one or more computers of the information retrieval system, a query in a first language, the first language being one of the target languages, after the translating and indexing of the documents and the anchor texts; and searching, by the search engine, the documents in the group that are in the first language, the translated documents that are in the first language, and the translated anchor texts that are in the first language to identify documents responsive to the query. 6. The non-transitory computer readable media of claim 5 , wherein: each document in the group of documents is a page on a respective web site and the context of each respective context-specific translation model depends on the text of all the pages on the web site or the text of pages that are linked to directly or indirectly from the document.
| 0.5 |
13. A computer-readable storage medium storing instructions thereon for executing a method, the method for extracting a representation of a state machine from a high-level integrated circuit description language, the method comprising: parsing the high-level integrated circuit description language; identifying processes within the integrated circuit description language; determining whether an identified process is a clock process by performing a processor-based search for a condition that changes a state of the process on a clock transition; building a state machine based in part on the identified clock process; and outputting a state machine description.
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13. A computer-readable storage medium storing instructions thereon for executing a method, the method for extracting a representation of a state machine from a high-level integrated circuit description language, the method comprising: parsing the high-level integrated circuit description language; identifying processes within the integrated circuit description language; determining whether an identified process is a clock process by performing a processor-based search for a condition that changes a state of the process on a clock transition; building a state machine based in part on the identified clock process; and outputting a state machine description. 20. The computer-readable storage medium of claim 13 , wherein the determining the clock process further comprises: checking a form of a clock clause; checking for an assignment to a state variable by the clock clause; and checking for a case statement test of the state variable.
| 0.550808 |
13. A method comprising: providing a policy enforcer executing at a first device; providing a first application program executing at the first device; providing a shared key ring at the first device wherein the shared key ring is associated with the policy enforcer and comprises at most one domain key and a plurality of shared keys; providing a file at the first device wherein the file further comprises a document content portion and a control data portion; extracting a content key from the control data portion; encrypting the document content portion using the content key; extracting a first key identifier from the control data portion; requesting from the policy enforcer a domain key; encrypting the control data portion of the file with the at most one domain key; at the first device, providing access to the file and its encrypted control data portion; intercepting at a second device a request to access the file at a second application program, wherein the intercepting the access of the encrypted document occurs at an system level of the application program comprising: allowing the access to the encrypted document by the application program to execute until a first system level operation executes; identifying the first system level operation as executing due to the application program requesting access to the encrypted document; and preventing the first system level operation from executing; determining at a policy enforcer executing at the second device whether the request to access the file at the second application program should be granted; and if the request to access the file at a second application program is granted, preparing the document content portion.
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13. A method comprising: providing a policy enforcer executing at a first device; providing a first application program executing at the first device; providing a shared key ring at the first device wherein the shared key ring is associated with the policy enforcer and comprises at most one domain key and a plurality of shared keys; providing a file at the first device wherein the file further comprises a document content portion and a control data portion; extracting a content key from the control data portion; encrypting the document content portion using the content key; extracting a first key identifier from the control data portion; requesting from the policy enforcer a domain key; encrypting the control data portion of the file with the at most one domain key; at the first device, providing access to the file and its encrypted control data portion; intercepting at a second device a request to access the file at a second application program, wherein the intercepting the access of the encrypted document occurs at an system level of the application program comprising: allowing the access to the encrypted document by the application program to execute until a first system level operation executes; identifying the first system level operation as executing due to the application program requesting access to the encrypted document; and preventing the first system level operation from executing; determining at a policy enforcer executing at the second device whether the request to access the file at the second application program should be granted; and if the request to access the file at a second application program is granted, preparing the document content portion. 14. The method of claim 13 wherein the preparing the document content portion comprises: decrypting the content key with the domain key; requesting from the policy enforcer a shared key from the key ring wherein the shared key is accessible by the second device; receiving the shared key; and encrypting the domain key with the shared key.
| 0.627072 |
16. A terminal comprising a device for enabling intelligent association in an input method, and the device comprising: a processor; and a memory coupled to the processor, the memory storing software units executable by the processor, the software units comprising: a receiving module configured to receive a first inputted keyboard code during a first time period and a second inputted keyboard code during a second time period after the first time period; a searching module configured to search for at least one first candidate character, using the first inputted keyboard code, from a preset lexicon, to generate at least one found first candidate character associated with the first inputted keyboard code, and search for at least one second candidate character using the second inputted keyboard code without the selected first character, from the preset lexicon, to generate at least one found second candidate character associated with the second inputted keyboard code, the receiving module being further configured to receive a selection of a first character from the at least one found first candidate character associated with the first inputted keyboard code; a calculating module configured to calculate a weight of each of the at least one found second candidate character associated with the second inputted keyboard code, the searching module being further configured to combine the selected first character with each of the at least one found second candidate character associated with the second inputted keyboard code, to respectively generate at least one combined key word, and search for the at least one combined key word, and the calculating module being further configured to calculate a weight of each of the at least one combined key word; an updating module configured to add the weight of each of the at least one found second candidate character associated with the second inputted keyboard code respectively to the weight of each of the at least one combined key word; and a displaying module configured to display the at least one found second candidate character, based on the weight of each of the at least one found second candidate character associated with the second inputted keyboard code respectively added to the weight of each of the at least one combined key word.
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16. A terminal comprising a device for enabling intelligent association in an input method, and the device comprising: a processor; and a memory coupled to the processor, the memory storing software units executable by the processor, the software units comprising: a receiving module configured to receive a first inputted keyboard code during a first time period and a second inputted keyboard code during a second time period after the first time period; a searching module configured to search for at least one first candidate character, using the first inputted keyboard code, from a preset lexicon, to generate at least one found first candidate character associated with the first inputted keyboard code, and search for at least one second candidate character using the second inputted keyboard code without the selected first character, from the preset lexicon, to generate at least one found second candidate character associated with the second inputted keyboard code, the receiving module being further configured to receive a selection of a first character from the at least one found first candidate character associated with the first inputted keyboard code; a calculating module configured to calculate a weight of each of the at least one found second candidate character associated with the second inputted keyboard code, the searching module being further configured to combine the selected first character with each of the at least one found second candidate character associated with the second inputted keyboard code, to respectively generate at least one combined key word, and search for the at least one combined key word, and the calculating module being further configured to calculate a weight of each of the at least one combined key word; an updating module configured to add the weight of each of the at least one found second candidate character associated with the second inputted keyboard code respectively to the weight of each of the at least one combined key word; and a displaying module configured to display the at least one found second candidate character, based on the weight of each of the at least one found second candidate character associated with the second inputted keyboard code respectively added to the weight of each of the at least one combined key word. 17. The terminal according to claim 16 , wherein the receiving module is further configured to receive either one or both of the first inputted keyboard code and the second inputted keyboard code through a keyboard.
| 0.50084 |
13. The system of claim 10 , wherein the hierarchical domain search engine is configured to adjust the reputability score according to traceability and association information associated with the domain.
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13. The system of claim 10 , wherein the hierarchical domain search engine is configured to adjust the reputability score according to traceability and association information associated with the domain. 15. The system of claim 13 wherein the traceability and association information identifies domains that require users to enter or disclose personal address information or credit card information prior to using a domain email address.
| 0.940245 |
1. A method of determining a geographical relevance of a document, performed by one or more processors associated with one or more server devices, the method comprising: generating, using a processor associated with the one or more server devices, a plurality of histograms associated with a plurality of respective strings in the document by comparing strings in the document to a pre-existing plurality of strings for which histograms were previously generated, where the plurality of histograms relates occurrences of strings to geographical regions; generating, using a processor associated with the one or more server devices, a combined histogram for the document from the plurality of histograms by multiplying together values for each histogram of the plurality of histograms; and identifying, using a processor associated with the one or more server devices, a geographical relevance of the document based on the combined histogram.
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1. A method of determining a geographical relevance of a document, performed by one or more processors associated with one or more server devices, the method comprising: generating, using a processor associated with the one or more server devices, a plurality of histograms associated with a plurality of respective strings in the document by comparing strings in the document to a pre-existing plurality of strings for which histograms were previously generated, where the plurality of histograms relates occurrences of strings to geographical regions; generating, using a processor associated with the one or more server devices, a combined histogram for the document from the plurality of histograms by multiplying together values for each histogram of the plurality of histograms; and identifying, using a processor associated with the one or more server devices, a geographical relevance of the document based on the combined histogram. 3. The method of claim 1 , where one or more strings in the plurality of strings comprise a single term string.
| 0.76834 |
15. The method of claim 12 , further comprising: pausing the audio/video report session, wherein the screen capture box is deactivated and the graphical user interface is activated; and accessing a radiology report of the radiographic images, wherein the audio/video report is a supplement to the radiology report.
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15. The method of claim 12 , further comprising: pausing the audio/video report session, wherein the screen capture box is deactivated and the graphical user interface is activated; and accessing a radiology report of the radiographic images, wherein the audio/video report is a supplement to the radiology report. 16. The method of claim 15 , further comprising: relaunching the audio/video report session, wherein the screen capture box is again activated, the video recording is again commenced, and the graphical user interface is again deactivated; and reinvoking audio dictation; and speaking further into the audio receiving device about the one or more radiographic images, wherein the received audio is recorded after the spoken words previously recorded.
| 0.796197 |
17. A computer readable storage medium, comprising executable instructions to: receive a query specification; receive a semantic abstraction associated with the query specification, wherein the semantic abstraction represents data source entities to be retrieved from an underlying data source; compute an execution plan, wherein the executable instructions to compute the execution plan comprise executable instructions to: evaluate the query specification to identify one or more of the data source entities to be retrieved; determine relationships between the data source entities; group data source entities into sets of compatible data source entities based on logical relationships between the data source entities; process operation instructions required by the query specification; and execute the execution plan, wherein the executable instructions to execute the execution plan comprise executable instructions to: retrieve a data flow associated with the query specification from a data source driver; and assemble the data flows into a query result set; and provide the query result set.
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17. A computer readable storage medium, comprising executable instructions to: receive a query specification; receive a semantic abstraction associated with the query specification, wherein the semantic abstraction represents data source entities to be retrieved from an underlying data source; compute an execution plan, wherein the executable instructions to compute the execution plan comprise executable instructions to: evaluate the query specification to identify one or more of the data source entities to be retrieved; determine relationships between the data source entities; group data source entities into sets of compatible data source entities based on logical relationships between the data source entities; process operation instructions required by the query specification; and execute the execution plan, wherein the executable instructions to execute the execution plan comprise executable instructions to: retrieve a data flow associated with the query specification from a data source driver; and assemble the data flows into a query result set; and provide the query result set. 30. The computer readable storage medium of claim 17 wherein the executable instructions to receive an entity relationship model associated with the query further comprise executable instructions to parse the query to determine which entity relationship model to retrieve and to retrieve the entity relationship model.
| 0.5 |
8. The handheld device of claim 7 wherein the first plurality of characters is a pair of letters of an alphabet and wherein the second plurality of characters is another pair of letters of the alphabet.
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8. The handheld device of claim 7 wherein the first plurality of characters is a pair of letters of an alphabet and wherein the second plurality of characters is another pair of letters of the alphabet. 9. The handheld device of claim 8 wherein the alphabet is of a language and wherein the displaying of one of the second plurality of characters comprises displaying the one of the second plurality of characters that is most likely to follow the displayed one of the first plurality of characters in the language.
| 0.881682 |
18. A server device an claimed in claim 17, further comprising an analysis result selection unit for selecting a specific one of the plurality of candidates displayed by the analysis result display unit and designating the specific one of the plurality of candidates an an analysis result.
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18. A server device an claimed in claim 17, further comprising an analysis result selection unit for selecting a specific one of the plurality of candidates displayed by the analysis result display unit and designating the specific one of the plurality of candidates an an analysis result. 19. A server device am claimed in claim 18, wherein the analysis result display unit displays each of the plurality of candidates generated by the source text analyzing unit as a sentence structure analysis tree.
| 0.936569 |
1. A method for generating a media presentation file containing composite media for display, the method comprising: generating a hierarchy of templates by at least one parent template receiving at least one child template comprised of a candidate template element received based upon a request and a search query for candidate template elements; interpreting one or more requests for at least one of media or templates in a framework template based on a user query input, wherein the framework template is comprised of the hierarchy of templates, wherein each template is comprised of corresponding slots for at least one of the candidate media elements and candidate template elements; executing one or more search queries based on the one or more requests for media or templates to locate and download candidates comprised of at least one of candidate media elements or candidate template elements; evaluating the candidates received from each of the one or more search queries to select winning media candidates comprised of selected candidate media elements and candidate template elements using design rules to change evaluation parameters associated with the candidates; and generating a media presentation file based on the defined presentation of composite media.
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1. A method for generating a media presentation file containing composite media for display, the method comprising: generating a hierarchy of templates by at least one parent template receiving at least one child template comprised of a candidate template element received based upon a request and a search query for candidate template elements; interpreting one or more requests for at least one of media or templates in a framework template based on a user query input, wherein the framework template is comprised of the hierarchy of templates, wherein each template is comprised of corresponding slots for at least one of the candidate media elements and candidate template elements; executing one or more search queries based on the one or more requests for media or templates to locate and download candidates comprised of at least one of candidate media elements or candidate template elements; evaluating the candidates received from each of the one or more search queries to select winning media candidates comprised of selected candidate media elements and candidate template elements using design rules to change evaluation parameters associated with the candidates; and generating a media presentation file based on the defined presentation of composite media. 4. The method of claim 1 , wherein the evaluation parameters comprise at least one of a statistical weight, previous use statistics, user ratings, candidate supplier rankings, or developer rankings.
| 0.617021 |
1. A method implemented by at least one computer processor, the method comprising: obtaining, from a client device of a user, a text message in a first language, the text message comprising at least one word; providing, using the at least one computer processor, the text message to a machine translation system; obtaining, using the at least one computer processor, a translation of the text message from the machine translation system; determining, using the at least one computer processor, that the text message and the translation both comprise the at least one word in the first language and that the at least one word is correctly spelled; and performing one or more of the following: (a) determining, using the at least one computer processor, Bayesian probabilities for neighboring words that appear before and after the at least one word and, when the Bayesian probabilities exceed a threshold value, adding the at least one word to a lexicon in a data store; and (b) performing, using the at least one computer processor, k-means clustering to identify a cluster of words comprising synonyms and, when the cluster comprises the at least one word, adding the at least one word to the lexicon in the data store.
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1. A method implemented by at least one computer processor, the method comprising: obtaining, from a client device of a user, a text message in a first language, the text message comprising at least one word; providing, using the at least one computer processor, the text message to a machine translation system; obtaining, using the at least one computer processor, a translation of the text message from the machine translation system; determining, using the at least one computer processor, that the text message and the translation both comprise the at least one word in the first language and that the at least one word is correctly spelled; and performing one or more of the following: (a) determining, using the at least one computer processor, Bayesian probabilities for neighboring words that appear before and after the at least one word and, when the Bayesian probabilities exceed a threshold value, adding the at least one word to a lexicon in a data store; and (b) performing, using the at least one computer processor, k-means clustering to identify a cluster of words comprising synonyms and, when the cluster comprises the at least one word, adding the at least one word to the lexicon in the data store. 5. The method of claim 1 , wherein the user is a player in an online game.
| 0.778068 |
25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities.
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25. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed on computer processor, facilitates searches for publications, by performing a method comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history representation between a plurality of different individuals and/or entities. 28. The computer-readable computer memory medium of claim 25 , the method further comprising: receiving a designation of a plurality of the search result snapshot objects; and merging the search results that correspond to each of the designated search result snapshot objects into a merged search result snapshot object.
| 0.524648 |
6. The computer-implemented method of claim 1 , further comprising re-training the classifier model based on the normalized score formula.
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6. The computer-implemented method of claim 1 , further comprising re-training the classifier model based on the normalized score formula. 7. The computer-implemented method of claim 6 , further comprising repeating the computer-implemented method with the re-trained classifier model.
| 0.905917 |
11. A system for building an integrated customer analytics solution for an enterprise comprising one or more data sources in a client-server architecture, wherein the system comprises one or more user devices and one or more servers for processing requests received from the one or more user devices, the system comprising: a data management module configured to: extract customer data from an operational data store, the operational data store storing the customer data in the form of data structures comprising one or more data fields gathered from the one or more data sources, wherein at least two data sources are disparate data sources which store data using different formats, and further wherein the extraction is performed to ascertain that the data structure corresponds to a predetermined data structure; transform the extracted customer data based on one or more predetermined formats; transform the existing one or more data fields of the operational data store into a first set of new data fields based on business specifications and requirement analysis of the enterprise; load the transformed customer data and the first set of new data fields into a data mart; and update the data mart with a second set of new data fields and new customer data corresponding to the second set of new data fields over a period of time of predetermined customer lifecycle stages, wherein the updating of the data mart is based on the business specifications and the requirement analysis of the enterprise; a statistical package module configured to: analyze the processed customer data stored in the data mart using one or more codes to generate one or more statistical techniques, the statistical techniques being at least one of descriptive statistics, cluster analysis, forecasting, survival analysis and logit model, wherein the one or more codes are developed using the statistical package module, and further wherein the generated one or more statistical techniques facilitate analyzing one or more predetermined attributes related to the customer; derive one or more statistical model outputs using the one or more generated statistical techniques, wherein the statistical model outputs represent one or more metrics corresponding to the analyzed attributes; generate one or more statistical models corresponding to the one or more statistical model outputs, the one or more statistical models being associated with one or more scores which are computed based on the statistical model outputs, wherein the one or more scores facilitate to predict likelihood of customer behavior towards products, services and other customer related aspects associated with the enterprise; and a reporting module configured to generate one or more reports based on the processed customer data stored in the data mart and the statistical model outputs, wherein one or more analytical modules are built for the predetermined customer lifecycle stages using the one or more reports and the one or more statistical models resulting in the integrated customer analytics solution.
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11. A system for building an integrated customer analytics solution for an enterprise comprising one or more data sources in a client-server architecture, wherein the system comprises one or more user devices and one or more servers for processing requests received from the one or more user devices, the system comprising: a data management module configured to: extract customer data from an operational data store, the operational data store storing the customer data in the form of data structures comprising one or more data fields gathered from the one or more data sources, wherein at least two data sources are disparate data sources which store data using different formats, and further wherein the extraction is performed to ascertain that the data structure corresponds to a predetermined data structure; transform the extracted customer data based on one or more predetermined formats; transform the existing one or more data fields of the operational data store into a first set of new data fields based on business specifications and requirement analysis of the enterprise; load the transformed customer data and the first set of new data fields into a data mart; and update the data mart with a second set of new data fields and new customer data corresponding to the second set of new data fields over a period of time of predetermined customer lifecycle stages, wherein the updating of the data mart is based on the business specifications and the requirement analysis of the enterprise; a statistical package module configured to: analyze the processed customer data stored in the data mart using one or more codes to generate one or more statistical techniques, the statistical techniques being at least one of descriptive statistics, cluster analysis, forecasting, survival analysis and logit model, wherein the one or more codes are developed using the statistical package module, and further wherein the generated one or more statistical techniques facilitate analyzing one or more predetermined attributes related to the customer; derive one or more statistical model outputs using the one or more generated statistical techniques, wherein the statistical model outputs represent one or more metrics corresponding to the analyzed attributes; generate one or more statistical models corresponding to the one or more statistical model outputs, the one or more statistical models being associated with one or more scores which are computed based on the statistical model outputs, wherein the one or more scores facilitate to predict likelihood of customer behavior towards products, services and other customer related aspects associated with the enterprise; and a reporting module configured to generate one or more reports based on the processed customer data stored in the data mart and the statistical model outputs, wherein one or more analytical modules are built for the predetermined customer lifecycle stages using the one or more reports and the one or more statistical models resulting in the integrated customer analytics solution. 12. The system of claim 11 , wherein the reporting module comprises a Jasper Reporting Tool.
| 0.565911 |
15. The apparatus according to claim 14 , further comprising: a rule modification interface to modify rules in the rule base and to add rules to the rule base.
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15. The apparatus according to claim 14 , further comprising: a rule modification interface to modify rules in the rule base and to add rules to the rule base. 16. The apparatus according to claim 15 , wherein: the rules stored in the rule base include textual language using a prescribed syntax, the textual language including a textual label separated from match terms and from negation terms with a prescribed symbol.
| 0.957492 |
9. A method comprising: receiving and storing an alert parameter from a member of a network, the alert parameter indicating a threshold number of views of a page; receiving an update from another member of the network, the update including at least page view data of a network of users, the network of users being comprised of first users who have previously interacted with a particular user of the network of users and second users who have previously interacted with the first users, each interaction being a prior commercial transaction or an electronic communication, each user of the network of users having conducted one or more prior commercial transactions with a business entity, the page view data indicating a number of views of the page by respective users of the network of users; retrieving the alert parameter, and comparing the alert parameter with the page view data included within the update; and transmitting an alert if the page view data exceeds the alert parameter.
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9. A method comprising: receiving and storing an alert parameter from a member of a network, the alert parameter indicating a threshold number of views of a page; receiving an update from another member of the network, the update including at least page view data of a network of users, the network of users being comprised of first users who have previously interacted with a particular user of the network of users and second users who have previously interacted with the first users, each interaction being a prior commercial transaction or an electronic communication, each user of the network of users having conducted one or more prior commercial transactions with a business entity, the page view data indicating a number of views of the page by respective users of the network of users; retrieving the alert parameter, and comparing the alert parameter with the page view data included within the update; and transmitting an alert if the page view data exceeds the alert parameter. 13. The method of claim 9 , further comprising: receiving a data request with a data identifier, the data request including at least a request for page view data; using the data identifier to determine a privilege to access data identified by the data request; retrieving the requested data based on the privilege; and transmitting the requested data.
| 0.647687 |
7. The computer-implemented method of claim 1 and further comprising: utilizing a lexicon to extract a third set of features for each unit in the normalized sequence of units; and wherein processing includes processing the data by also using the third set of features in the classification model.
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7. The computer-implemented method of claim 1 and further comprising: utilizing a lexicon to extract a third set of features for each unit in the normalized sequence of units; and wherein processing includes processing the data by also using the third set of features in the classification model. 8. The computer-implemented method of claim 7 wherein one of the features in the third set of features includes a percentage of words in the normalized sequence of units that are end-of-sentence words, and wherein a second one of the features in the third set of features includes a percentage of words in the normalized sequence of units that are not in the lexicon.
| 0.854206 |
1. A method in a computing system for improving the relevance of search results retrieved from one or more keyword-based search engines, comprising: receiving an indication of a designated entity having a name; determining whether the name of the designated entity is likely to lead to relevancy errors when used in a keyword-based search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; when determined that the name of the designated entity is likely to lead to relevancy errors, determining whether the name of the designated entity should be enhanced with an entity-specific enhancement, a facet-specific enhancement, or both types of enhancements, to formulate an enhanced query strategy, wherein the enhanced query strategy comprises a plurality of automatically generated queries that include disambiguation information, wherein an entity-specific enhancement includes a name of an entity, action, or property value related to the designated entity or related through a facet of the designated entity, and wherein a facet-specific enhancement includes one or more terms related to a facet; and when determined that the name of the designated entity is to be enhanced to formulate the enhanced query strategy, using one or more query enhancer components of the computing system selected based upon the determination of whether the name of the designated entity is to be enhanced with the entity-specific enhancement and/or the facet-specific enhancement, automatically adding one or more entity-specific queries and/or one or more facet-specific queries to the name of the designated entity to generate the enhanced query strategy, wherein at least one of the enhancements is based upon one or more facets associated with the designated entity; and forwarding the automatically generated query strategy to the one or more keyword-based search engines to generate on-topic information related to the designated entity.
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1. A method in a computing system for improving the relevance of search results retrieved from one or more keyword-based search engines, comprising: receiving an indication of a designated entity having a name; determining whether the name of the designated entity is likely to lead to relevancy errors when used in a keyword-based search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; when determined that the name of the designated entity is likely to lead to relevancy errors, determining whether the name of the designated entity should be enhanced with an entity-specific enhancement, a facet-specific enhancement, or both types of enhancements, to formulate an enhanced query strategy, wherein the enhanced query strategy comprises a plurality of automatically generated queries that include disambiguation information, wherein an entity-specific enhancement includes a name of an entity, action, or property value related to the designated entity or related through a facet of the designated entity, and wherein a facet-specific enhancement includes one or more terms related to a facet; and when determined that the name of the designated entity is to be enhanced to formulate the enhanced query strategy, using one or more query enhancer components of the computing system selected based upon the determination of whether the name of the designated entity is to be enhanced with the entity-specific enhancement and/or the facet-specific enhancement, automatically adding one or more entity-specific queries and/or one or more facet-specific queries to the name of the designated entity to generate the enhanced query strategy, wherein at least one of the enhancements is based upon one or more facets associated with the designated entity; and forwarding the automatically generated query strategy to the one or more keyword-based search engines to generate on-topic information related to the designated entity. 14. The method of claim 1 wherein the automatically generated query strategy is used with a keyword-based search engine API for searching videos.
| 0.566985 |
1. A non-transitory data storage device having program instructions stored thereon for a graphical user interface for a system for querying web data, comprising: program instructions for a query entry component visually rendered in a display of computer system, wherein the query entry component is defined to receive textual input of a query language (QL) statement, wherein the QL statement identifies one or more QL tables associated with one or more web data sources, wherein each of the one or more QL tables includes binding data which includes instructions for a QL web service on creating a universal resource locator (URL) to access and retrieve data from a web data source, and for interfacing with the web data source and interacting with the web data source in order to query the web data source for specific data present at the web data source, and wherein the binding data of each of the one or more QL tables informs the QL web service as to what types of data are present within the web data source; program instructions for a results data display component visually rendered in the display, wherein the results data display component is defined to visually display results data obtained from execution of the QL statement present in the query entry component; and program instructions for a QL web service URL conveyance component visually rendered in the display, wherein the QL web service URL conveyance component is defined to visually and electronically convey a QL web service URL defined to access one or more QL tables identified in the QL statement through the Internet and retrieve direction from the one or more QL tables regarding access and retrieval of data from the one or more web data sources associated with the one or more QL tables identified in the QL statement.
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1. A non-transitory data storage device having program instructions stored thereon for a graphical user interface for a system for querying web data, comprising: program instructions for a query entry component visually rendered in a display of computer system, wherein the query entry component is defined to receive textual input of a query language (QL) statement, wherein the QL statement identifies one or more QL tables associated with one or more web data sources, wherein each of the one or more QL tables includes binding data which includes instructions for a QL web service on creating a universal resource locator (URL) to access and retrieve data from a web data source, and for interfacing with the web data source and interacting with the web data source in order to query the web data source for specific data present at the web data source, and wherein the binding data of each of the one or more QL tables informs the QL web service as to what types of data are present within the web data source; program instructions for a results data display component visually rendered in the display, wherein the results data display component is defined to visually display results data obtained from execution of the QL statement present in the query entry component; and program instructions for a QL web service URL conveyance component visually rendered in the display, wherein the QL web service URL conveyance component is defined to visually and electronically convey a QL web service URL defined to access one or more QL tables identified in the QL statement through the Internet and retrieve direction from the one or more QL tables regarding access and retrieval of data from the one or more web data sources associated with the one or more QL tables identified in the QL statement. 3. The data storage device as recited in claim 1 , wherein the results data is generated by operating a QL web service to execute the QL web service URL.
| 0.556965 |
1. A computer implemented method, comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file providing a source name identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; invoking a generator with a reference to the model file; processing, by the invoked generator, the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; determining instances of the source name indicated in the model file in the data structure; and generating, for the determined instances of the source name in the data structure, a reference in the data structure schema to the reusable code identified by the source name, wherein the reference generated in the data structure schema includes the element and attribute information indicated in the model file.
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1. A computer implemented method, comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file providing a source name identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; invoking a generator with a reference to the model file; processing, by the invoked generator, the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; determining instances of the source name indicated in the model file in the data structure; and generating, for the determined instances of the source name in the data structure, a reference in the data structure schema to the reusable code identified by the source name, wherein the reference generated in the data structure schema includes the element and attribute information indicated in the model file. 3. The method of claim 1 , wherein the generator is invoked to generate multiple data structure schemas in the second programming language for multiple data structures coded in the first programming language, wherein the same generated reference to the reusable code is included in the multiple schemas.
| 0.62663 |
16. A system for converting a natural language sentence into a computer-readable primitive sentence, the system comprising: a processing device; and a non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: identify a verbal block in the natural language sentence; split the natural language sentence into one or more logical clauses; determine a type for each of the one or more logical clauses, wherein the type indicates whether each of the one or more logical clauses contains an ambiguous verbal block; disambiguate the ambiguous verbal block within each of the one or more logical clauses, wherein each verbal block is considered independently of a noun phrase; and construct the computer-readable primitive sentence for each ambiguous verbal block by duplicating a shared noun phrase of the ambiguous verbal block, wherein the computer-readable primitive sentence improves a functioning of a computing device by not requiring voluminous storage space in allowing the computing device to process the natural language sentence to obtain information from the natural language sentence.
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16. A system for converting a natural language sentence into a computer-readable primitive sentence, the system comprising: a processing device; and a non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: identify a verbal block in the natural language sentence; split the natural language sentence into one or more logical clauses; determine a type for each of the one or more logical clauses, wherein the type indicates whether each of the one or more logical clauses contains an ambiguous verbal block; disambiguate the ambiguous verbal block within each of the one or more logical clauses, wherein each verbal block is considered independently of a noun phrase; and construct the computer-readable primitive sentence for each ambiguous verbal block by duplicating a shared noun phrase of the ambiguous verbal block, wherein the computer-readable primitive sentence improves a functioning of a computing device by not requiring voluminous storage space in allowing the computing device to process the natural language sentence to obtain information from the natural language sentence. 20. The system of claim 16 , wherein the one or more programming instructions that, when executed, cause the processing device to disambiguate the ambiguous verbal block further comprise causing the processing device to perform at least one of a local disambiguating task and a global disambiguating task.
| 0.537853 |
4. The method of claim 3 , wherein the set of generalized terms includes at least one broader term corresponding to the at least one term of the query.
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4. The method of claim 3 , wherein the set of generalized terms includes at least one broader term corresponding to the at least one term of the query. 5. The method of claim 4 , wherein generating the plurality of subqueries further comprises: computing the sensitivity score for each sensitive term; and upon determining the sensitivity score for the respective sensitive term exceeds a threshold, restricting the plurality of subqueries from including the respective sensitive term.
| 0.926311 |
1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value.
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1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. 14. The system of claim 1 , wherein the generic decoder is configured for branching through directed parsing.
| 0.656318 |
11. The method of claim 10 , further comprising the step of computing a reduced rank approximation based on the selected singular values and the selected singular vectors, the reduced rank approximation providing an index for use during information retrieval.
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11. The method of claim 10 , further comprising the step of computing a reduced rank approximation based on the selected singular values and the selected singular vectors, the reduced rank approximation providing an index for use during information retrieval. 14. The method of claim 11 , wherein the selecting step comprises selecting at least one of the actual singular values of matrix A that substantially equal at least one of the estimated singular values corresponding to at least one of the probabilistic distributions on parts.
| 0.85048 |
11. A method for identifying electronic documents stored on a computer readable media, and providing a search result in response to a search query, comprising: receiving a search query; identifying a predetermined number of documents that satisfy the search query, the predetermined number of documents including reference documents which are a subset of the identified documents that are deemed to be the most relevant to the search query and secondary documents; parsing text excerpts of the identified documents and applying text function tags to the text excerpts, wherein the text function tags identify semantic roles of the text excerpts; identifying the secondary documents that have text function tags that match the text function tags of a reference document; and generating a search engine results page in response to the search query, the search engine results page including a listing of the identified reference documents, each with a hyperlink to at least one secondary document, the at least one secondary document being a secondary document that has a text function tag that matches a text function tag of the reference document.
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11. A method for identifying electronic documents stored on a computer readable media, and providing a search result in response to a search query, comprising: receiving a search query; identifying a predetermined number of documents that satisfy the search query, the predetermined number of documents including reference documents which are a subset of the identified documents that are deemed to be the most relevant to the search query and secondary documents; parsing text excerpts of the identified documents and applying text function tags to the text excerpts, wherein the text function tags identify semantic roles of the text excerpts; identifying the secondary documents that have text function tags that match the text function tags of a reference document; and generating a search engine results page in response to the search query, the search engine results page including a listing of the identified reference documents, each with a hyperlink to at least one secondary document, the at least one secondary document being a secondary document that has a text function tag that matches a text function tag of the reference document. 16. The method of claim 11 , further including ignoring predetermined text function tags.
| 0.665661 |
1. A method of recognizing speech, the method comprising: receiving speech utterances; determining via a processor a probable acoustic environment of the user based on time of day; compensating a speech recognition model based on the probable acoustic environment; and recognizing the speech utterances using the compensated speech recognition model.
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1. A method of recognizing speech, the method comprising: receiving speech utterances; determining via a processor a probable acoustic environment of the user based on time of day; compensating a speech recognition model based on the probable acoustic environment; and recognizing the speech utterances using the compensated speech recognition model. 6. The method according to claim 1 , wherein the data of the particular acoustic environmental is received from a personal digital assistant.
| 0.660377 |
1. A computer-implemented method comprising acts of: receiving, via at least one network, adaptation data generated at least in part by performing statistical processing on audio data comprising at least one user utterance; and using the adaptation data to update at least one acoustic model for use in speech recognition processing, wherein the adaptation data is in a format that prevents reconstruction of the audio data.
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1. A computer-implemented method comprising acts of: receiving, via at least one network, adaptation data generated at least in part by performing statistical processing on audio data comprising at least one user utterance; and using the adaptation data to update at least one acoustic model for use in speech recognition processing, wherein the adaptation data is in a format that prevents reconstruction of the audio data. 3. The computer-implemented method of claim 1 , wherein: the adaptation data comprises first adaptation data received from a first device and second adaptation data received from a second device different from the first device; and the act of using the adaptation data comprises aggregating the first adaptation data and the second adaptation data.
| 0.727106 |
24. The method of claim 23 , wherein the television broadcast is provided by a broadband provider.
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24. The method of claim 23 , wherein the television broadcast is provided by a broadband provider. 25. The method of claim 24 , wherein the broadband provider is a triple play or quad play service provider.
| 0.953003 |
3. The PDM data processing system of claim 1 , further comprises: provide the library, wherein the library acts as a container for all library hierarchies and library nodes related to the library and comprises at least one library hierarchy; provide the at least one library hierarchy, wherein each of the at least one library hierarchy provides a hierarchical organization to structure a plurality of library nodes; and provide a library element, wherein the library element exposes the library object to the library.
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3. The PDM data processing system of claim 1 , further comprises: provide the library, wherein the library acts as a container for all library hierarchies and library nodes related to the library and comprises at least one library hierarchy; provide the at least one library hierarchy, wherein each of the at least one library hierarchy provides a hierarchical organization to structure a plurality of library nodes; and provide a library element, wherein the library element exposes the library object to the library. 4. The PDM data processing system of claim 3 , further comprising: classify the library with a classification hierarchy, wherein the classification hierarchy provides a hierarchical organization to structure groups and classes.
| 0.865829 |
1. An adaptive recommendation system, comprising: a content aspect comprising information; a computer-implemented structural aspect comprising the content aspect and associated relationships; a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users of the system; a function to generate a user tunable adaptive recommendation based, at least in part, on a user's navigational context and on an automatic inference of the user's interests from a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories; and a function to deliver the adaptive recommendation to the user.
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1. An adaptive recommendation system, comprising: a content aspect comprising information; a computer-implemented structural aspect comprising the content aspect and associated relationships; a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users of the system; a function to generate a user tunable adaptive recommendation based, at least in part, on a user's navigational context and on an automatic inference of the user's interests from a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories; and a function to deliver the adaptive recommendation to the user. 9. The adaptive recommendation system of claim 1 , wherein a function to generate a user tunable adaptive recommendation based, at least in part, on a user's navigational context and on an automatic inference of the user's interests from a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories comprises: a function that infers user preferences from usage behaviors.
| 0.621622 |
13. A computer readable storage medium having computer-executable instructions for evaluating a semantic proximity between a question consisting of a string of natural language text presented in a candidate free-form text request received from a user, and a reference free-form text entry consisting of a string of natural language text, comprising: providing a plurality of reference free-form text entries in a data store, each entry in the form of a question expressed as a string of natural language text associated with an answer to the question; receiving a candidate free-form text request from a user work station in the form of a query expressed as a string of natural language text; processing the string of natural language text expressed in each reference free-form text entry into a plurality of reference rephrased objects, each reference rephrased object containing a variation of the string of natural language text expressed in the reference free-form text entry and an expression of the semantic proximity between the variation of the string of natural language text contained in the reference rephrased object and the string of natural language text expressed in the reference free-form text entry; processing the string of natural language text expressed in the candidate free-form text request into a plurality of user rephrased objects, each user rephrased object containing a variation of the string of natural language text expressed in the candidate free-form text request and an expression of the semantic proximity between the variation of the string of natural language text contained in the user rephrased object and the string of natural language text expressed in the candidate free-form text request; matching at least one of the reference rephrased objects derived from the processing of the reference free-form text entry with at least one user rephrased objects derived from the processing of the candidate free-form text request; and calculating a combined semantic proximity for each matching reference rephrased object and user rephrased object.
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13. A computer readable storage medium having computer-executable instructions for evaluating a semantic proximity between a question consisting of a string of natural language text presented in a candidate free-form text request received from a user, and a reference free-form text entry consisting of a string of natural language text, comprising: providing a plurality of reference free-form text entries in a data store, each entry in the form of a question expressed as a string of natural language text associated with an answer to the question; receiving a candidate free-form text request from a user work station in the form of a query expressed as a string of natural language text; processing the string of natural language text expressed in each reference free-form text entry into a plurality of reference rephrased objects, each reference rephrased object containing a variation of the string of natural language text expressed in the reference free-form text entry and an expression of the semantic proximity between the variation of the string of natural language text contained in the reference rephrased object and the string of natural language text expressed in the reference free-form text entry; processing the string of natural language text expressed in the candidate free-form text request into a plurality of user rephrased objects, each user rephrased object containing a variation of the string of natural language text expressed in the candidate free-form text request and an expression of the semantic proximity between the variation of the string of natural language text contained in the user rephrased object and the string of natural language text expressed in the candidate free-form text request; matching at least one of the reference rephrased objects derived from the processing of the reference free-form text entry with at least one user rephrased objects derived from the processing of the candidate free-form text request; and calculating a combined semantic proximity for each matching reference rephrased object and user rephrased object. 18. The computer readable storage medium of claim 13 , wherein the processing applied to convert a reference free-form text entry into the list of reference rephrased objects is the same as the processing applied to convert a candidate free-form text request into a list of user rephrased objects.
| 0.506882 |
1. A method of presenting news content to a user with a computing system comprising: a) determining a first user geographic region associated with the user; b) automatically determining a target geographic region for a first event with the computing system by analyzing content for news stories relating to said first event; c) determining if said first event in said target geographic region is related to said first user geographic region; d) automatically selecting one or more local sources with the computing system to collect local content for stories associated with said first event; wherein said one or more local sources include news sources within or proximate to said target geographic region; e) presenting news stories to a user for said first user geographic region with the computing system within a graphical interface based on a news ranking determined for said news stories; wherein for said presenting step (e) said local content from said local sources is given a higher news ranking than content from other reference content sources by the computing system at least for stories that are associated with said first event.
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1. A method of presenting news content to a user with a computing system comprising: a) determining a first user geographic region associated with the user; b) automatically determining a target geographic region for a first event with the computing system by analyzing content for news stories relating to said first event; c) determining if said first event in said target geographic region is related to said first user geographic region; d) automatically selecting one or more local sources with the computing system to collect local content for stories associated with said first event; wherein said one or more local sources include news sources within or proximate to said target geographic region; e) presenting news stories to a user for said first user geographic region with the computing system within a graphical interface based on a news ranking determined for said news stories; wherein for said presenting step (e) said local content from said local sources is given a higher news ranking than content from other reference content sources by the computing system at least for stories that are associated with said first event. 6. The method of claim 1 wherein a set of additional local sources is predicted and selected from a prediction of story developments for said event.
| 0.801858 |
3. The method of claim 2 , further comprising: comparing the at least one representation to the at least one stored image of the object; and determining a similarity metric based on the comparison.
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3. The method of claim 2 , further comprising: comparing the at least one representation to the at least one stored image of the object; and determining a similarity metric based on the comparison. 4. The method of claim 3 , further comprising generating a heat map, wherein the heat map is based on the similarity metric.
| 0.966595 |
15. A device, comprising: at least one processor and a memory; the at least one processor configured to: during program development, create a data structure representing source code, the data structure generated by a background compiler, wherein at least one inferred symbol is added to the data structure based on source code entered in a source code editor wherein the at least one inferred symbol is inferred from the source code based on usage of a symbol without prior definition of the symbol; during program development, utilizing the at least one inferred symbol in a tool that is part of the source code editor, wherein the tool displays the inferred symbol for the user's use in developing source code; and during program development, convert the at least one inferred symbol to a real symbol in the data structure response to receiving an indication from a user to convert the at least one inferred symbol to the real symbol.
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15. A device, comprising: at least one processor and a memory; the at least one processor configured to: during program development, create a data structure representing source code, the data structure generated by a background compiler, wherein at least one inferred symbol is added to the data structure based on source code entered in a source code editor wherein the at least one inferred symbol is inferred from the source code based on usage of a symbol without prior definition of the symbol; during program development, utilizing the at least one inferred symbol in a tool that is part of the source code editor, wherein the tool displays the inferred symbol for the user's use in developing source code; and during program development, convert the at least one inferred symbol to a real symbol in the data structure response to receiving an indication from a user to convert the at least one inferred symbol to the real symbol. 18. The device of claim 15 , wherein the at least one processor is further configured to: display information associated with the at least one inferred symbol in software development tools in response to activation of an option in a programming environment.
| 0.559322 |
1. A method for scripting via an interface to a programmable processing device, comprising the steps of: providing an interface to one or more programmable processing units communicatively coupled to each other in a programmable processing device comprising a script input tool for inputting one or more scripts and a file input tool for inputting one or more first original multimedia items for batch manipulation by the one or more programmable processing units; accepting from the script input tool an input of one or more scripts, said scripts written in a scripting language, said scripting language comprising variables representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items; accepting from the file input tool a representation of one or more first original multimedia items; creating an association between the first original multimedia items and said input scripts; and storing the association in a container file comprising the input scripts and the first original multimedia items wherein the container file acts as a proxy for one or more result multimedia items after the manipulation has been applied, wherein the container file as the proxy is referenced to render the one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation.
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1. A method for scripting via an interface to a programmable processing device, comprising the steps of: providing an interface to one or more programmable processing units communicatively coupled to each other in a programmable processing device comprising a script input tool for inputting one or more scripts and a file input tool for inputting one or more first original multimedia items for batch manipulation by the one or more programmable processing units; accepting from the script input tool an input of one or more scripts, said scripts written in a scripting language, said scripting language comprising variables representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items; accepting from the file input tool a representation of one or more first original multimedia items; creating an association between the first original multimedia items and said input scripts; and storing the association in a container file comprising the input scripts and the first original multimedia items wherein the container file acts as a proxy for one or more result multimedia items after the manipulation has been applied, wherein the container file as the proxy is referenced to render the one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation. 11. The method of claim 1 wherein creating an association is performed in batches of multimedia items.
| 0.542434 |
18. The correlator of claim 13 wherein means for forming said correlator output signals comprises: first storing means for storing each of said ramp weighted segment sums over said plurality of word periods; second storing means for storing uniformly weighted segment sums over said plurality of word periods; first scaling means for scaling a sequence of said stored ramp weighted segment sums by +1 or -1 to represent the up slope or down slope of triangular weights to achieve said triangular weighting; second scaling means for scaling a sequence of said stored uniformly weighted segment sums by an appropriate integer value to represent an offset between a ramp and said triangular weighting within said segment; accumulating means for accumulating said scaled ramp weighted segment sums and said scaled uniformly weighted sums with appropriate normalization factors to provide said correlator output signal for a particular word segment.
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18. The correlator of claim 13 wherein means for forming said correlator output signals comprises: first storing means for storing each of said ramp weighted segment sums over said plurality of word periods; second storing means for storing uniformly weighted segment sums over said plurality of word periods; first scaling means for scaling a sequence of said stored ramp weighted segment sums by +1 or -1 to represent the up slope or down slope of triangular weights to achieve said triangular weighting; second scaling means for scaling a sequence of said stored uniformly weighted segment sums by an appropriate integer value to represent an offset between a ramp and said triangular weighting within said segment; accumulating means for accumulating said scaled ramp weighted segment sums and said scaled uniformly weighted sums with appropriate normalization factors to provide said correlator output signal for a particular word segment. 22. The correlator of claim 18 wherein said scaled, stored ramp-weighted segment sums are accumulated to provide a ramp-weighted accumulated value, and further comprising means for applying a normalization factor a1 to said ramp-weighted accumulated value.
| 0.789698 |
13. The system as recited in claim 1 , further comprising logic configured to detect an attempt to initiate a financial transaction using the financial document.
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13. The system as recited in claim 1 , further comprising logic configured to detect an attempt to initiate a financial transaction using the financial document. 14. The system as recited in claim 13 , further comprising logic configured to prompt the user to capture the image of the financial document in response to detecting the attempt to initiate the financial transaction.
| 0.950087 |
1. A method, performed by at least one computer system, of retrieving documents in response to a search query submitted on a first date that includes one or more phrases, the method comprising: selecting from a corpus of documents a plurality of documents that include at least one of the one or more phrases and that are relevant to the query based on a relevance score for the selected documents; determining, using a processor of the at least one computer system, for at least one of the selected documents, a date range for the document, the date range representing a period for which no change in the document has been detected; calculating, using a processor of the at least one computer system, a weighted relevance score for each of the selected documents, the weighted relevance score for a particular document being based on the relevance score for the particular document and a difference between the first date and the date range for the particular document; and ranking, using a processor of the at least one computer system, the selected documents according to their weighted relevance scores.
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1. A method, performed by at least one computer system, of retrieving documents in response to a search query submitted on a first date that includes one or more phrases, the method comprising: selecting from a corpus of documents a plurality of documents that include at least one of the one or more phrases and that are relevant to the query based on a relevance score for the selected documents; determining, using a processor of the at least one computer system, for at least one of the selected documents, a date range for the document, the date range representing a period for which no change in the document has been detected; calculating, using a processor of the at least one computer system, a weighted relevance score for each of the selected documents, the weighted relevance score for a particular document being based on the relevance score for the particular document and a difference between the first date and the date range for the particular document; and ranking, using a processor of the at least one computer system, the selected documents according to their weighted relevance scores. 6. The method of claim 1 , wherein the search query includes a date term and the weighted relevance score for the particular document is based on a function of the date term and the date range for the particular document.
| 0.568858 |
1. A method for operating an automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: performing a first task using a first parameter; providing a first response to a user based on a result of performing the first task using the first parameter; in a first operation: obtaining a first text string from a first speech input received from the user; determining whether the first text string includes a second task different from the first task, where the first text string does not include a recitation of the first parameter; and in accordance with a determination that the first text string includes the second task different from the first task and does not include a recitation of the first parameter: performing the second task using the first parameter; and providing a second response to the user based on a result of performing the second task using the first parameter; and in a second operation: obtaining a second text string from a second speech input received from the user; determining whether the second text string includes a second parameter different from the first parameter, where the second text string does not include a recitation of the first task; in accordance with a determination that the second text string includes the second parameter different from the first parameter and does not include a recitation of the first task: performing the first task using the second parameter; and providing a third response to the user based on a result of performing the first task using the second parameter.
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1. A method for operating an automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: performing a first task using a first parameter; providing a first response to a user based on a result of performing the first task using the first parameter; in a first operation: obtaining a first text string from a first speech input received from the user; determining whether the first text string includes a second task different from the first task, where the first text string does not include a recitation of the first parameter; and in accordance with a determination that the first text string includes the second task different from the first task and does not include a recitation of the first parameter: performing the second task using the first parameter; and providing a second response to the user based on a result of performing the second task using the first parameter; and in a second operation: obtaining a second text string from a second speech input received from the user; determining whether the second text string includes a second parameter different from the first parameter, where the second text string does not include a recitation of the first task; in accordance with a determination that the second text string includes the second parameter different from the first parameter and does not include a recitation of the first task: performing the first task using the second parameter; and providing a third response to the user based on a result of performing the first task using the second parameter. 11. The method of claim 1 , wherein the first task is a restaurant reservation task.
| 0.595859 |
1. A computer-implemented method of providing access to information stored in diverse formats, the method comprising: receiving from an application a semantic request having a request name that semantically identifies a type of information sought by the request, the semantic request comprising a uniform resource identifier; converting, at a semantic object provider, the received semantic request to a generic request having corresponding request parameters, the semantic object provider comprising a semantic object class defining an application programming interface to create an object, a semantic object implementation class to provide persistency to information related to a class, and an object registry to interact with a class implemented by a repository; initiating, by the semantic object provider, a creation of the object for receiving and converting the semantic request; opening a database connection within a data access system corresponding to the semantic request; requesting properties of data corresponding to the semantic request, if a database connection has not previously been opened; transmitting the converted request to the a data access system; receiving data from the data access system corresponding to the converted request; and providing the data to the application.
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1. A computer-implemented method of providing access to information stored in diverse formats, the method comprising: receiving from an application a semantic request having a request name that semantically identifies a type of information sought by the request, the semantic request comprising a uniform resource identifier; converting, at a semantic object provider, the received semantic request to a generic request having corresponding request parameters, the semantic object provider comprising a semantic object class defining an application programming interface to create an object, a semantic object implementation class to provide persistency to information related to a class, and an object registry to interact with a class implemented by a repository; initiating, by the semantic object provider, a creation of the object for receiving and converting the semantic request; opening a database connection within a data access system corresponding to the semantic request; requesting properties of data corresponding to the semantic request, if a database connection has not previously been opened; transmitting the converted request to the a data access system; receiving data from the data access system corresponding to the converted request; and providing the data to the application. 5. The computer-implemented method of claim 1 , wherein the converted request comprises parameters corresponding to, but not present in, the semantic request.
| 0.598522 |
1. A method of improving classification accuracy and reducing false positives in data mining, computer aided-detection, computer-aided diagnosis and artificial intelligence, the method comprising: choosing a training set from a set of training cases using systematic data scaling, the training set including one or more training cases for true nodules and one or more training cases for false nodules, the systematic data scaling removing only one or more training cases for false nodules, which is proximate a classification boundary for true and false nodules, from the training set; and, creating a classifier based on the training set using a classification method, wherein the systematic data scaling method and the classification method produce the classifier thereby reducing false positives and improving classification accuracy.
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1. A method of improving classification accuracy and reducing false positives in data mining, computer aided-detection, computer-aided diagnosis and artificial intelligence, the method comprising: choosing a training set from a set of training cases using systematic data scaling, the training set including one or more training cases for true nodules and one or more training cases for false nodules, the systematic data scaling removing only one or more training cases for false nodules, which is proximate a classification boundary for true and false nodules, from the training set; and, creating a classifier based on the training set using a classification method, wherein the systematic data scaling method and the classification method produce the classifier thereby reducing false positives and improving classification accuracy. 6. The method according to claim 1 wherein the method further comprises validating the classifier with the set of training cases or a subset thereof.
| 0.59439 |
13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: generating a user identifier using a voice request, the voice request received from a device; estimating, via successive comparisons, a transducer noise parameter of the device, wherein a delay between the successive comparisons is increased when successive changes do not exceed a threshold value; comparing stored user identities to the user identifier, to yield a comparison; when, based on the comparison, a user is associated with the device: retrieving a parameterizable speech recognition model associated with the user identifier; and adapting the parameterizable speech recognition model based on the transducer noise parameter to yield an adapted parameterizable speech recognition model; and performing speech recognition on the voice request using the adapted parameterizable speech recognition model.
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13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: generating a user identifier using a voice request, the voice request received from a device; estimating, via successive comparisons, a transducer noise parameter of the device, wherein a delay between the successive comparisons is increased when successive changes do not exceed a threshold value; comparing stored user identities to the user identifier, to yield a comparison; when, based on the comparison, a user is associated with the device: retrieving a parameterizable speech recognition model associated with the user identifier; and adapting the parameterizable speech recognition model based on the transducer noise parameter to yield an adapted parameterizable speech recognition model; and performing speech recognition on the voice request using the adapted parameterizable speech recognition model. 16. The computer-readable storage device of claim 13 , wherein the parameterizable speech recognition model is generated based on a background model, a transducer model, and the user identifier.
| 0.515315 |
1. A method of operating a data processing system to examine a compiled program for violations of a set of rules that do not constitute violations detected by a compiler used to compile the compiled program, said method comprising: obtaining a restricted rule set defined in terms of rules in a decompiled representation of said program, said restricted rule set prohibiting language commands that would otherwise be allowed by said compiler in a subset of classes in said compiled program while allowing said language commands in another class of said program; decompiling said compiled program to said decompiled representation of said compiled program in which said restricted rule set is defined; examining said decompiled representation of said compiled program for a violation of said restricted rule set to determine if any of said rules are violated; and providing an output indicating that one of said rules was violated, wherein said restricted rule set only applies to a portion of said compiled program and wherein decompiling said compiled program comprises decompiling said portion of said compiled program while not decompiling another portion of said compiled program, said portion of said compiled program comprising a set of sub-classes of a class, and wherein decompiling said program comprises identifying a location in said compiled program of instructions pertaining to said set of sub-classes, said data processing system generating a certificate if said compiled program does not violate said restricted rule set.
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1. A method of operating a data processing system to examine a compiled program for violations of a set of rules that do not constitute violations detected by a compiler used to compile the compiled program, said method comprising: obtaining a restricted rule set defined in terms of rules in a decompiled representation of said program, said restricted rule set prohibiting language commands that would otherwise be allowed by said compiler in a subset of classes in said compiled program while allowing said language commands in another class of said program; decompiling said compiled program to said decompiled representation of said compiled program in which said restricted rule set is defined; examining said decompiled representation of said compiled program for a violation of said restricted rule set to determine if any of said rules are violated; and providing an output indicating that one of said rules was violated, wherein said restricted rule set only applies to a portion of said compiled program and wherein decompiling said compiled program comprises decompiling said portion of said compiled program while not decompiling another portion of said compiled program, said portion of said compiled program comprising a set of sub-classes of a class, and wherein decompiling said program comprises identifying a location in said compiled program of instructions pertaining to said set of sub-classes, said data processing system generating a certificate if said compiled program does not violate said restricted rule set. 3. The method of claim 1 wherein said compiled program further comprises metadata that identifies locations in said compiled program of methods pertaining to said set of sub-classes.
| 0.558549 |
10. In computer-implemented apparatus, the apparatus having a processor and a memory, the memory having computer executable instructions stored therein, a method for recommending an item to a particular one of a plurality of users, the item not yet rated by the user, the method comprising steps, performed through the executable instructions, of: (a) generating, for the particular one user, a concept mask representing areas of interest of the one user; (b) storing, in the memory, a user profile in a memory for each of a plurality of users, wherein the user profile of the user includes a plurality of values, each of the plurality of values representing a rating given to one of a plurality of items by the user; (c) calculating, for each of the plurality of users, a plurality of similarity factor vectors representing the similarity between each user and another one of the plurality of users for at least one concept specified within the concept mask; (d) selecting, for each of the plurality of users, a plurality of neighboring users based on the similarity factor vectors; (e) assigning a weight to each of the neighboring users so as to define a plurality of weights assigned to the neighboring users; and (f) recommending at least one of the plurality of items to the particular one user based on the weights assigned to the neighboring users and the ratings given to the non-rated item by the neighboring users.
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10. In computer-implemented apparatus, the apparatus having a processor and a memory, the memory having computer executable instructions stored therein, a method for recommending an item to a particular one of a plurality of users, the item not yet rated by the user, the method comprising steps, performed through the executable instructions, of: (a) generating, for the particular one user, a concept mask representing areas of interest of the one user; (b) storing, in the memory, a user profile in a memory for each of a plurality of users, wherein the user profile of the user includes a plurality of values, each of the plurality of values representing a rating given to one of a plurality of items by the user; (c) calculating, for each of the plurality of users, a plurality of similarity factor vectors representing the similarity between each user and another one of the plurality of users for at least one concept specified within the concept mask; (d) selecting, for each of the plurality of users, a plurality of neighboring users based on the similarity factor vectors; (e) assigning a weight to each of the neighboring users so as to define a plurality of weights assigned to the neighboring users; and (f) recommending at least one of the plurality of items to the particular one user based on the weights assigned to the neighboring users and the ratings given to the non-rated item by the neighboring users. 14. The method of claim 10 wherein the concept mask includes every concept with which rated items are associated.
| 0.722057 |
3. The system of claim 1 , wherein the acoustic elements in the one or more series divide the one or more represented syllables into one or more core components.
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3. The system of claim 1 , wherein the acoustic elements in the one or more series divide the one or more represented syllables into one or more core components. 5. The system of claim 3 , wherein the acoustic elements in the one or more series further divide the one or more core components associated with the one or more represented syllables into one or more sub-categories.
| 0.893732 |
12. The method in claim 9 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class.
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12. The method in claim 9 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class. 15. The method in claim 12 wherein the authoring attributes comprise whether the incoming message contains an address of a single recipient, or contains addresses of plurality of recipients or contains no sender at all, or a time at which the incoming message was transmitted.
| 0.879018 |
1. An anchor assembly comprising: an anchor body with an anchor; an anchor head including a U-shaped yoke having two arms; a first aperture in the first arm and a second aperture in the second arm; and a shaft spanning a gap between the two arms of the yoke; a saddle mounting element mounted about said shaft; a saddle having a transverse bore and a longitudinal bore which intersects the transverse bore; the saddle mounting element being received in the transverse bore of the saddle such that a portion of the saddle extends around the saddle mounting element between the saddle mounting element and the anchor head such that the saddle is secured to the anchor head and can move relative to the anchor head; said saddle having a slot adapted to hold a member; a set that is received in said saddle and can be selectively advanced into the slot; whereby, with a member received in the slot, advancing the set into the slot forces the member against the saddle mounting element thereby securing the member to the saddle and fixing the saddle relative to the anchor head.
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1. An anchor assembly comprising: an anchor body with an anchor; an anchor head including a U-shaped yoke having two arms; a first aperture in the first arm and a second aperture in the second arm; and a shaft spanning a gap between the two arms of the yoke; a saddle mounting element mounted about said shaft; a saddle having a transverse bore and a longitudinal bore which intersects the transverse bore; the saddle mounting element being received in the transverse bore of the saddle such that a portion of the saddle extends around the saddle mounting element between the saddle mounting element and the anchor head such that the saddle is secured to the anchor head and can move relative to the anchor head; said saddle having a slot adapted to hold a member; a set that is received in said saddle and can be selectively advanced into the slot; whereby, with a member received in the slot, advancing the set into the slot forces the member against the saddle mounting element thereby securing the member to the saddle and fixing the saddle relative to the anchor head. 7. The anchor assembly of claim 1 wherein the saddle mounting element is cylindrical.
| 0.706872 |
4. The method of claim 1 , wherein generating a textual representation of the received spoken audio input comprises: extracting phonemes from the received spoken audio input; and generating a textual representation of the extracted phonemes.
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4. The method of claim 1 , wherein generating a textual representation of the received spoken audio input comprises: extracting phonemes from the received spoken audio input; and generating a textual representation of the extracted phonemes. 5. The method of claim 4 , wherein extracting phonemes from the received spoken audio input comprises: determining the language of the received spoken audio input; and extracting phonemes from the received spoken audio input based on the determined language.
| 0.873204 |
18. The method of claim 13 , further comprising: re-testing, by the microprocessor, a subset of the list of text names when a spelling of a name in the list of text names is changed, a new name is added to the list of text names, or an existing name is deleted from the list of text names.
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18. The method of claim 13 , further comprising: re-testing, by the microprocessor, a subset of the list of text names when a spelling of a name in the list of text names is changed, a new name is added to the list of text names, or an existing name is deleted from the list of text names. 19. The method of claim 18 , wherein names that were not correctly identified by the top match or scored below the first threshold when previously tested are recursively re-tested.
| 0.923982 |
11. The method of claim 3 , wherein the detecting includes dynamically detecting a position of at least one tag.
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11. The method of claim 3 , wherein the detecting includes dynamically detecting a position of at least one tag. 20. The method of claim 11 , wherein the detecting comprises assigning a position of each tag to a subset of points that form a single tag.
| 0.880435 |
1. A method of sharing in one or more network(s), the method comprising: storing and managing each registered user's one or more profile(s), IN and OUT permission and relational connections or dynamic relationships in a non-transitory computer readable memory of a central server; mapping or requesting sharing of one or more selected contents by one or more requestor or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; determining one or more target users by requestor(s) or sharing user(s) with the said request including share selected one or more contents from one or more network(s) with or via one or more selected communication channels or services, applications or modules, connections or relations from set of requestor(s) or sharing user(s) related subscribed communication channels or services, installed applications or modules and connected or related users; receiving, storing and processing one or more shared contents with metadata including determined target users of requestor(s) or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; matching by the central server a target user with the requestor or sharing user, wherein the matching is conducted by the central server based on one or more selections, IN and OUT preferences, profiles and connections of requestor(s) or sharing user(s); and providing or synchronizing or updating said one or more shared contents of said requestor(s) or sharing user(s) from one or more network(s) to said determined one or more target users.
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1. A method of sharing in one or more network(s), the method comprising: storing and managing each registered user's one or more profile(s), IN and OUT permission and relational connections or dynamic relationships in a non-transitory computer readable memory of a central server; mapping or requesting sharing of one or more selected contents by one or more requestor or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; determining one or more target users by requestor(s) or sharing user(s) with the said request including share selected one or more contents from one or more network(s) with or via one or more selected communication channels or services, applications or modules, connections or relations from set of requestor(s) or sharing user(s) related subscribed communication channels or services, installed applications or modules and connected or related users; receiving, storing and processing one or more shared contents with metadata including determined target users of requestor(s) or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; matching by the central server a target user with the requestor or sharing user, wherein the matching is conducted by the central server based on one or more selections, IN and OUT preferences, profiles and connections of requestor(s) or sharing user(s); and providing or synchronizing or updating said one or more shared contents of said requestor(s) or sharing user(s) from one or more network(s) to said determined one or more target users. 12. The method as claimed in claim 1 , wherein monitoring and recording of each user's sharing related each actions and events with accessible metadata or fields or parameters and synchronizing related actions and events with accessible metadata or fields or parameters to related or connected and subscribed users.
| 0.556257 |
1. A system embodied upon computer readable storage media for previewing visual changes of a web portal, the system comprising: an administrative component that generates a preview document in response to a request, wherein the preview document is a web page, and wherein the administrative component provides portal configuration information that contains functional characteristics for the web portal and a set of temporary files that provide one or more presentation characteristics for the web portal; a preview document that utilizes the portal configuration information for the functional characteristics of the portal and the temporary files for the presentation characteristics of the web portal, and wherein the preview document includes an instruction set that when processed by an application at a client renders the preview document in a web browser; wherein when a cursor, at the web browser, is positioned over one of said one or more sections of the web portal, the instruction set is read and executed by the application to present, in a graphical overlay at the web browser, an identity of the one or more style properties affecting the one of said one or more sections while the cursor is positioned over the one of said one or more sections, wherein the one or more style properties affecting the section is derived from a structured style sheet, and wherein the identity of the one or more style properties affecting the section includes an indication of whether the one or more style properties is inherited; and wherein upon receiving a modification to the set of temporary files that changes the one or more style properties affecting the presentation characteristics of the web portal, a request is sent to accept modifications to the set of temporary files, and wherein accepting the modifications initiates a copy process to update the portal configuration information to include the set of temporary files as modified.
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1. A system embodied upon computer readable storage media for previewing visual changes of a web portal, the system comprising: an administrative component that generates a preview document in response to a request, wherein the preview document is a web page, and wherein the administrative component provides portal configuration information that contains functional characteristics for the web portal and a set of temporary files that provide one or more presentation characteristics for the web portal; a preview document that utilizes the portal configuration information for the functional characteristics of the portal and the temporary files for the presentation characteristics of the web portal, and wherein the preview document includes an instruction set that when processed by an application at a client renders the preview document in a web browser; wherein when a cursor, at the web browser, is positioned over one of said one or more sections of the web portal, the instruction set is read and executed by the application to present, in a graphical overlay at the web browser, an identity of the one or more style properties affecting the one of said one or more sections while the cursor is positioned over the one of said one or more sections, wherein the one or more style properties affecting the section is derived from a structured style sheet, and wherein the identity of the one or more style properties affecting the section includes an indication of whether the one or more style properties is inherited; and wherein upon receiving a modification to the set of temporary files that changes the one or more style properties affecting the presentation characteristics of the web portal, a request is sent to accept modifications to the set of temporary files, and wherein accepting the modifications initiates a copy process to update the portal configuration information to include the set of temporary files as modified. 4. The system of claim 1 , wherein a name of the one or more style properties affecting the section is presented in the graphical overlay.
| 0.570295 |
15. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; wherein a version of the first content item is stored at the user computer at the time the search query is obtained; wherein the first search answer summary indicates that the version of the first content item stored at the user computer is older than a version of the first content item hosted by the online content management service; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item.
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15. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; wherein a version of the first content item is stored at the user computer at the time the search query is obtained; wherein the first search answer summary indicates that the version of the first content item stored at the user computer is older than a version of the first content item hosted by the online content management service; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. 16. The method of claim 15 , further comprising: displaying, by at least one of the processors, in the graphical user interface at the user computer, for at least a third content item in the first set of one or more of the user's hosted content items that satisfy the search query, a third search answer summary for the third content item; wherein the third content item is not stored at the user computer at the time the search query is obtained; and wherein the third search answer summary indicates that the third content item is not stored at the user computer.
| 0.528571 |
1. A method of controlling an ambient characteristic of at least one ambient device, the method comprising acts of: providing an ambient control system connected to a database having a plurality of files including multimedia content having a specific ambiance and a textual description of the ambiance, the database is selected from one or more locally and network connected databases; receiving a textual description of a desired ambiance as an input from an operator of the ambient control system; compiling a list of files of the plurality of files based on a match between the received textual description and the textual description of the files by dividing each file into regions and obtaining localized values for each region as part of a plurality of ambient parameters; for each file in the list of files identifying a plurality of ambient parameters corresponding to the received textual description, and determining an average value of each of the plurality of ambient parameters; creating an association between the received textual description and the average values of the plurality of ambient parameters including region information of the ambient parameters; and controlling the ambient characteristic of the at least one ambient device based on the association and selecting the multimedia content to display in a room based on the association, wherein the ambient characteristic includes background sound, and scent.
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1. A method of controlling an ambient characteristic of at least one ambient device, the method comprising acts of: providing an ambient control system connected to a database having a plurality of files including multimedia content having a specific ambiance and a textual description of the ambiance, the database is selected from one or more locally and network connected databases; receiving a textual description of a desired ambiance as an input from an operator of the ambient control system; compiling a list of files of the plurality of files based on a match between the received textual description and the textual description of the files by dividing each file into regions and obtaining localized values for each region as part of a plurality of ambient parameters; for each file in the list of files identifying a plurality of ambient parameters corresponding to the received textual description, and determining an average value of each of the plurality of ambient parameters; creating an association between the received textual description and the average values of the plurality of ambient parameters including region information of the ambient parameters; and controlling the ambient characteristic of the at least one ambient device based on the association and selecting the multimedia content to display in a room based on the association, wherein the ambient characteristic includes background sound, and scent. 2. The method of claim 1 , wherein the plurality of ambient parameters comprises one or more of light value, color value, sound indicator, and background noise indicator.
| 0.725446 |
16. A method, implemented at a portable electronic device with a touch screen display, comprising: displaying at least a portion of a structured electronic document on the touch screen display, wherein the structured electronic document comprises a plurality of boxes of content and the displayed portion includes at least a first box of content and a second box of content, the first box of content being displayed at a location on the touch screen display that is separate from a location of the second box of content; detecting a first gesture at a location on the displayed portion of the structured electronic document; and in response to detecting the first gesture: in accordance with the first gesture being located at the first box of content in the plurality of boxes of content, enlarging and translating the structured electronic document so that the first box of content is displayed on the touch screen display and the second box of content is not displayed on the touch screen display; in accordance with the first gesture being located at the second box of content in the plurality of boxes of content, enlarging and translating the structured electronic document so that the second box of content is displayed on the touch screen display and the first box of content is not displayed on the touch screen display.
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16. A method, implemented at a portable electronic device with a touch screen display, comprising: displaying at least a portion of a structured electronic document on the touch screen display, wherein the structured electronic document comprises a plurality of boxes of content and the displayed portion includes at least a first box of content and a second box of content, the first box of content being displayed at a location on the touch screen display that is separate from a location of the second box of content; detecting a first gesture at a location on the displayed portion of the structured electronic document; and in response to detecting the first gesture: in accordance with the first gesture being located at the first box of content in the plurality of boxes of content, enlarging and translating the structured electronic document so that the first box of content is displayed on the touch screen display and the second box of content is not displayed on the touch screen display; in accordance with the first gesture being located at the second box of content in the plurality of boxes of content, enlarging and translating the structured electronic document so that the second box of content is displayed on the touch screen display and the first box of content is not displayed on the touch screen display. 25. The method of claim 16 , wherein the displayed portion of the structured electronic document before said detecting of the first gesture comprises a third box of content displayed adjacent to the first box of content in a different location on the touch screen display to the second box of content, the method further comprising, in response to detecting the first gesture when the first gesture is located at the first box of content, enlarging and translating the structured electronic document so that a portion of the third box of content is displayed on the touch screen display.
| 0.55864 |
9. A speech processing system comprising: a processor; and a memory coupled to the processor, the memory comprising: a communication module configured to receive speech sample in Oriya English for speech recognition; a data analysis module configured to: determine values of a plurality of speech parameters for the received sample based on Fujisaki model, wherein the values of the plurality of speech parameters comprises base frequencies of the speech samples, phrase components of the speech samples, and associated accent components with the speech samples, wherein each of the speech samples are processed by filtering each of the speech samples using different linear filters, and wherein the linear filters model a baseline component which corresponds to speaker declination and model a micro-prosodic variations which corresponds to the accent components of each of the speech samples; and a data processing module configured to recognize the speech sample based on governing language rules through Hidden Markov Model (HMM).
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9. A speech processing system comprising: a processor; and a memory coupled to the processor, the memory comprising: a communication module configured to receive speech sample in Oriya English for speech recognition; a data analysis module configured to: determine values of a plurality of speech parameters for the received sample based on Fujisaki model, wherein the values of the plurality of speech parameters comprises base frequencies of the speech samples, phrase components of the speech samples, and associated accent components with the speech samples, wherein each of the speech samples are processed by filtering each of the speech samples using different linear filters, and wherein the linear filters model a baseline component which corresponds to speaker declination and model a micro-prosodic variations which corresponds to the accent components of each of the speech samples; and a data processing module configured to recognize the speech sample based on governing language rules through Hidden Markov Model (HMM). 10. The speech processing system as claimed in claim 9 , wherein the data processing module is further configured to: generate text in accordance with the recognized speech sample, wherein the text is independent of Oriya English phonetic variations and mother tongue influence; and synthesize natural speech based on the generated text, wherein the synthesized natural speech is induced with Oriya English accent based on the phonetic variations of Oriya English determined through the speech parameters.
| 0.666959 |
15. A computing device, comprising: at least one processor; and a computer-readable storage medium comprising computer-executable instructions which when executed cause the at least one processor to: extract metadata from server-side source code of a server project of an application, wherein the extracted metadata comprises at least one server-side program entity exposed to a client-side project by the server project and wherein the extracted metadata does not comprise a program entity that is not exposed to the client-side project; extract additional metadata from the server-side source code, wherein the additional extracted metadata comprises at least one additional server-side program entity referenced by the at least one server-side program entity; replace a program entity in the extracted metadata or in the additional extracted metadata that is not defined in the server-side source code with a marked inferred program entity, where the marked inferred program entity represents a program entity whose absence would prevent the successful compiling of the server-side source code; convert the extracted metadata and the additional extracted metadata to libraries comprising metadata, without compiling the server-side source code; and display documentation and disambiguation information associated with the at least one server-side program entity derived from the libraries in a source code editor during development of client-side source code for the application and not display documentation and disambiguation information associated with the library derived from the marked inferred program entity.
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15. A computing device, comprising: at least one processor; and a computer-readable storage medium comprising computer-executable instructions which when executed cause the at least one processor to: extract metadata from server-side source code of a server project of an application, wherein the extracted metadata comprises at least one server-side program entity exposed to a client-side project by the server project and wherein the extracted metadata does not comprise a program entity that is not exposed to the client-side project; extract additional metadata from the server-side source code, wherein the additional extracted metadata comprises at least one additional server-side program entity referenced by the at least one server-side program entity; replace a program entity in the extracted metadata or in the additional extracted metadata that is not defined in the server-side source code with a marked inferred program entity, where the marked inferred program entity represents a program entity whose absence would prevent the successful compiling of the server-side source code; convert the extracted metadata and the additional extracted metadata to libraries comprising metadata, without compiling the server-side source code; and display documentation and disambiguation information associated with the at least one server-side program entity derived from the libraries in a source code editor during development of client-side source code for the application and not display documentation and disambiguation information associated with the library derived from the marked inferred program entity. 18. The computing device of claim 15 wherein the computer-readable storage medium further comprises computer-executable instructions, which when executed cause the at least one processor to: not generate client-side source code for a client project of the application for the marked inferred program entity.
| 0.564485 |
1. A method of connecting to a virtual community based on any web resource in the Internet being accessed by at least one user, the method comprising: providing a browser plugin or helper object operable to: integrate with the at least one user's web browser; detect the at least one user's browsing activities; automatically create a virtual community for users to interact and to store meta information for said web resource corresponding to any accessed web resource if said user is a first user to access said web resource and said virtual community does not yet exist, otherwise, join to an existing virtual community corresponding to said accessed web resource; start a connection between the at least one user's web browser and the virtual community based on the presently accessed web resource; and retrieve information related to the virtual community; and allow community members to communicate with users outside said virtual community using said connections.
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1. A method of connecting to a virtual community based on any web resource in the Internet being accessed by at least one user, the method comprising: providing a browser plugin or helper object operable to: integrate with the at least one user's web browser; detect the at least one user's browsing activities; automatically create a virtual community for users to interact and to store meta information for said web resource corresponding to any accessed web resource if said user is a first user to access said web resource and said virtual community does not yet exist, otherwise, join to an existing virtual community corresponding to said accessed web resource; start a connection between the at least one user's web browser and the virtual community based on the presently accessed web resource; and retrieve information related to the virtual community; and allow community members to communicate with users outside said virtual community using said connections. 3. The method of claim 1 , wherein the browser plugin or helper object is provided either manually or automatically without the at least one user's intervention.
| 0.558469 |
1. A method for automatically acquiring a digital copy of a song that is being received over a radio channel and played on a device, the method comprising: receiving, at the device, user preferences for purchasing digital copies of songs, the user preferences including a minimum bitrate for the digital copies; receiving, at the device, a transmission of a radio channel that is currently playing a song; tuning the device to the radio channel such that the song is played on the device; while the song is being played, receiving user input that requests that a digital copy of the song being played be acquired; analyzing the data, associated with the song, that is transmitted over the radio channel to determine one or more characteristics of the song being played; using the determined one or more characteristics to search over the internet a plurality of audio content providers to locate a digital copy of the song that is available to be purchased at each of the plurality of audio content providers; receiving information from each of the plurality of audio content providers that indicate characteristics of the digital copy of the song that is available to be purchased at the audio content provider, the characteristics including at least a price and a bitrate of the digital copy of the song; using the user preferences stored on the device to automatically determine which of the digital copies of the song is to be purchased including selecting digital copies having a bitrate that at least equals the minimum bitrate specified by the user preferences, and selecting a least expensive digital copy from among the digital copies that have a bitrate that at least equals the minimum bitrate; and upon purchasing the automatically determined digital copy, downloading, to the device, the automatically determined digital copy of the song from the corresponding audio content provider.
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1. A method for automatically acquiring a digital copy of a song that is being received over a radio channel and played on a device, the method comprising: receiving, at the device, user preferences for purchasing digital copies of songs, the user preferences including a minimum bitrate for the digital copies; receiving, at the device, a transmission of a radio channel that is currently playing a song; tuning the device to the radio channel such that the song is played on the device; while the song is being played, receiving user input that requests that a digital copy of the song being played be acquired; analyzing the data, associated with the song, that is transmitted over the radio channel to determine one or more characteristics of the song being played; using the determined one or more characteristics to search over the internet a plurality of audio content providers to locate a digital copy of the song that is available to be purchased at each of the plurality of audio content providers; receiving information from each of the plurality of audio content providers that indicate characteristics of the digital copy of the song that is available to be purchased at the audio content provider, the characteristics including at least a price and a bitrate of the digital copy of the song; using the user preferences stored on the device to automatically determine which of the digital copies of the song is to be purchased including selecting digital copies having a bitrate that at least equals the minimum bitrate specified by the user preferences, and selecting a least expensive digital copy from among the digital copies that have a bitrate that at least equals the minimum bitrate; and upon purchasing the automatically determined digital copy, downloading, to the device, the automatically determined digital copy of the song from the corresponding audio content provider. 4. The method of claim 1 wherein analyzing data associated with the song comprises extracting metadata about the song, the metadata including one or more of a title, an artist, a genre, or an album of the song.
| 0.84384 |
1. A computer implemented method comprising: obtaining metadata for a document, wherein the metadata includes a sequence of terms; assigning a tag to each term in the sequence of terms based at least in part on grammatical relationships between the terms, resulting in a corresponding sequence of tags; determining that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags; in response to the determination, storing the sequence of terms as a query suggestion within a database of query suggestions; in response to the determination, further calculating a suggestion score for the query suggestion based on one or more data points, and wherein storing the query suggestion includes storing the suggestion score with the query suggestion; receiving a partial search query; selecting one or more query suggestions in the database for the partial search query based at least in part on the suggestion scores; and sending the selected query suggestions in response to receiving the partial search query; wherein obtaining metadata for the document comprises segmenting the metadata for the document into a plurality of sequences of terms, wherein at least two of the plurality of sequences include at least some identical terms in different orders; and wherein assigning a tag comprises assigning a tag to each term in a given sequence of terms in the plurality of sequences of terms.
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1. A computer implemented method comprising: obtaining metadata for a document, wherein the metadata includes a sequence of terms; assigning a tag to each term in the sequence of terms based at least in part on grammatical relationships between the terms, resulting in a corresponding sequence of tags; determining that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags; in response to the determination, storing the sequence of terms as a query suggestion within a database of query suggestions; in response to the determination, further calculating a suggestion score for the query suggestion based on one or more data points, and wherein storing the query suggestion includes storing the suggestion score with the query suggestion; receiving a partial search query; selecting one or more query suggestions in the database for the partial search query based at least in part on the suggestion scores; and sending the selected query suggestions in response to receiving the partial search query; wherein obtaining metadata for the document comprises segmenting the metadata for the document into a plurality of sequences of terms, wherein at least two of the plurality of sequences include at least some identical terms in different orders; and wherein assigning a tag comprises assigning a tag to each term in a given sequence of terms in the plurality of sequences of terms. 7. The computer implemented method of claim 1 , wherein determining that the sequence of terms is grammatically correct is based at least in part on an order of the tags within the corresponding sequence of tags.
| 0.782209 |
1. One or more computer-readable storage media having computer-executable instructions for performing a method comprising: in a first pane for a node, presenting a representation of the node and one or more links from the node to other nodes adjacent to the node in a graph data structure; and responsive to activation of one of the links presented in the first pane from the node to a selected node, presenting in a second pane adjacent to the first pane, a representation of the node for the activated link and one or more links from the node for the activated link to other nodes adjacent to the node for the activated link in the graph data structure; wherein in the second pane, the one or more links from the node for the activated link to other nodes comprise a link back to the node of the first pane; and wherein each of the first pane and the second pane further comprises a title of a node the pane represents and an additional description of a node the pane represents.
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1. One or more computer-readable storage media having computer-executable instructions for performing a method comprising: in a first pane for a node, presenting a representation of the node and one or more links from the node to other nodes adjacent to the node in a graph data structure; and responsive to activation of one of the links presented in the first pane from the node to a selected node, presenting in a second pane adjacent to the first pane, a representation of the node for the activated link and one or more links from the node for the activated link to other nodes adjacent to the node for the activated link in the graph data structure; wherein in the second pane, the one or more links from the node for the activated link to other nodes comprise a link back to the node of the first pane; and wherein each of the first pane and the second pane further comprises a title of a node the pane represents and an additional description of a node the pane represents. 5. The one or more computer-readable storage media of claim 1 wherein: the presenting presents links for all adjacent nodes.
| 0.530086 |
7. A system for hierarchically partitioning a data set including a plurality of offerings, comprising: a data processing system having a partition hierarchy module, the data processing system further comprising a memory storing processor-executable instructions; and a processor configured to execute the processor-executable instructors to: receive a data set including a plurality of offerings, each of the offerings characterized by one or more offering attributes; identify one or more advertising performance metric goals for the data set; determine, based on the identified advertising performance metric goals for the data set, a first offering attribute and a first plurality of attribute values of the first offering attribute according to which to partition the offerings across a first plurality of partition groups; determine, based on the identified advertising performance metric goals for the data set, a second offering attribute and a second plurality of attribute values of the second offering attribute according to which to further partition offerings included in a first subset of the first plurality of partition groups; determine, based on the identified advertising performance metric goals for the data set, a third plurality of attribute values of a third offering attribute according to which to further partition offerings included in a second subset of the first plurality of partition groups; partition the plurality of offerings across the first plurality of partition groups; partition the plurality of offerings included in the first subset of the first plurality of partition groups across the second plurality of partition groups; and partition the plurality of offerings included in the second subset of the first plurality of partition groups across the third plurality of partition groups.
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7. A system for hierarchically partitioning a data set including a plurality of offerings, comprising: a data processing system having a partition hierarchy module, the data processing system further comprising a memory storing processor-executable instructions; and a processor configured to execute the processor-executable instructors to: receive a data set including a plurality of offerings, each of the offerings characterized by one or more offering attributes; identify one or more advertising performance metric goals for the data set; determine, based on the identified advertising performance metric goals for the data set, a first offering attribute and a first plurality of attribute values of the first offering attribute according to which to partition the offerings across a first plurality of partition groups; determine, based on the identified advertising performance metric goals for the data set, a second offering attribute and a second plurality of attribute values of the second offering attribute according to which to further partition offerings included in a first subset of the first plurality of partition groups; determine, based on the identified advertising performance metric goals for the data set, a third plurality of attribute values of a third offering attribute according to which to further partition offerings included in a second subset of the first plurality of partition groups; partition the plurality of offerings across the first plurality of partition groups; partition the plurality of offerings included in the first subset of the first plurality of partition groups across the second plurality of partition groups; and partition the plurality of offerings included in the second subset of the first plurality of partition groups across the third plurality of partition groups. 12. The system of claim 7 , wherein to determine the first offering attribute and the first plurality of attribute values of the first offering attribute according to which to partition the offerings across a first plurality of partition groups the processor: identifies bid history associated with the offerings; determines, from the bid history, one or more bid value ranges, the bid value ranges including one or more average bid values associated with the attribute values; and groups attribute values corresponding to a bid value range of the bid value ranges.
| 0.55847 |
9. A computer program product, comprising a computer readable storage medium having a computer readable program code stored therein, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method of analyzing a problem in a computing environment, said method comprising: generating, by a computing system, a plurality of symptom rules in a symptom catalog that includes a plurality of sets of information (problem information) about a plurality of problems, wherein said plurality of symptom rules includes a plurality of sets of keywords, wherein said symptom catalog associates said sets of keywords to said sets of problem information in a one-to-one correspondence, and wherein said generating said plurality of symptom rules includes: receiving a document that includes a plurality of tagged keywords included in a prior stack trace, wherein said plurality of tagged keywords indicate said problem; identifying a range of lines in said document, wherein said range of lines indicates said prior stack trace; identifying said plurality of tagged keywords in a set of contiguous lines within said range of lines; extracting said plurality of tagged keywords from said set of contiguous lines; in response to said extracting, converting said plurality of tagged keywords into a plurality of expressions that facilitate said matching; and subsequent to said converting, storing said plurality of expressions in a symptom rule of said plurality of symptom rules residing in a computer data storage device; receiving, by said computing system, an input file that includes a stack trace provided in response to a detection of said problem; identifying, by said computing system, a set of function names included in a plurality of contiguous lines in said stack trace; searching, by said computing system, said symptom catalog for said set of function names; matching, by said computing system and in response to said searching, said set of function names to a set of keywords of said plurality of sets of keywords; retrieving, by said computing system, a set of problem information of said plurality of sets of problem information, wherein said set of problem information corresponds to said set of keywords and includes a solution to said problem; and generating, by said computing system, a report that includes said stack trace and said solution, wherein said report displays said set of function names included in said stack trace in a text having at least one attribute that emphasizes said text.
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9. A computer program product, comprising a computer readable storage medium having a computer readable program code stored therein, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method of analyzing a problem in a computing environment, said method comprising: generating, by a computing system, a plurality of symptom rules in a symptom catalog that includes a plurality of sets of information (problem information) about a plurality of problems, wherein said plurality of symptom rules includes a plurality of sets of keywords, wherein said symptom catalog associates said sets of keywords to said sets of problem information in a one-to-one correspondence, and wherein said generating said plurality of symptom rules includes: receiving a document that includes a plurality of tagged keywords included in a prior stack trace, wherein said plurality of tagged keywords indicate said problem; identifying a range of lines in said document, wherein said range of lines indicates said prior stack trace; identifying said plurality of tagged keywords in a set of contiguous lines within said range of lines; extracting said plurality of tagged keywords from said set of contiguous lines; in response to said extracting, converting said plurality of tagged keywords into a plurality of expressions that facilitate said matching; and subsequent to said converting, storing said plurality of expressions in a symptom rule of said plurality of symptom rules residing in a computer data storage device; receiving, by said computing system, an input file that includes a stack trace provided in response to a detection of said problem; identifying, by said computing system, a set of function names included in a plurality of contiguous lines in said stack trace; searching, by said computing system, said symptom catalog for said set of function names; matching, by said computing system and in response to said searching, said set of function names to a set of keywords of said plurality of sets of keywords; retrieving, by said computing system, a set of problem information of said plurality of sets of problem information, wherein said set of problem information corresponds to said set of keywords and includes a solution to said problem; and generating, by said computing system, a report that includes said stack trace and said solution, wherein said report displays said set of function names included in said stack trace in a text having at least one attribute that emphasizes said text. 12. The program product of claim 9 , wherein said method further comprises: receiving, by said computing system, a second input file that includes a second stack trace provided in response to a detection of a second problem, wherein said second stack trace includes multiple sets of function names included in multiple sets of contiguous lines included in said second stack trace; determining, by said computing system, that no set of function names of said multiple sets of function names match any set of keywords of said plurality of sets of keywords; determining, by said computing system, that a problem code in said second input file indicates that a new symptom rule can be generated for said second problem; identifying, by said computing system and based on said problem code, a first new set of function names of said multiple sets of function names, wherein said first new set of function names is included in a first set of contiguous lines of said multiple sets of contiguous lines, and wherein said first new set of function names indicates a first symptom of said second problem; and storing, by said computing system, said first new set of function names in a first new symptom rule in said symptom catalog.
| 0.5 |
1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized.
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1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized. 7. The method of claim 1 , wherein the loudness measurement includes determining if the input signal is clipped.
| 0.577281 |
19. The method of claim 15 , further comprising: determining, by the system, a mutated metaphor as a result of applying a mutator to the metaphor; generating, by the system, a mutated code segment corresponding to the mutated metaphor; and facilitating, by the system, access to the mutated code segment.
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19. The method of claim 15 , further comprising: determining, by the system, a mutated metaphor as a result of applying a mutator to the metaphor; generating, by the system, a mutated code segment corresponding to the mutated metaphor; and facilitating, by the system, access to the mutated code segment. 22. The method of claim 19 , further comprising: determining, by the system, a deviation in performance between execution of the code segment and execution of the mutated code segment; and facilitating, by the system, access to information related to the deviation in performance.
| 0.812782 |
1. A method for providing a personalized network based dialogue, comprising: storing a script associated with a campaign and a set of user information for a user selected for the campaign, the script specifying a plurality of events; executing a first instruction according to the script, wherein the first instruction is operable to send a first communication to the user from a server; determining a value for a variable associated with an event specified by the script, wherein the determination of the value is based on an interaction with the first communication by the user; determining a second instruction according to the script based on the set of user information and the value for the variable associated with the event specified by the script; and executing the second instruction to send a second communication to the user from the server.
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1. A method for providing a personalized network based dialogue, comprising: storing a script associated with a campaign and a set of user information for a user selected for the campaign, the script specifying a plurality of events; executing a first instruction according to the script, wherein the first instruction is operable to send a first communication to the user from a server; determining a value for a variable associated with an event specified by the script, wherein the determination of the value is based on an interaction with the first communication by the user; determining a second instruction according to the script based on the set of user information and the value for the variable associated with the event specified by the script; and executing the second instruction to send a second communication to the user from the server. 3. The method of claim 1 , wherein the set of user information is obtained from a user interaction with an email.
| 0.644167 |
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