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8. A system, comprising: a network device comprising a first processor and configured to manage a messaging component for receiving and sending messages over a network; and a tagging component residing on another network device comprising a second processor, the tagging component operative to perform actions, including: receiving a message having at least one attachment from the messaging component; using a machine learning model to select at least one sentence from within the message to be relevant to the at least one attachment based on a set of predefined sentence level features; identifying from within the at least one relevant sentences a set of keywords further relevant to the at least one attachment; and associating at least one of the keywords in the set to the at least one attachment, such that the association is useable for at least one of indexing or searching of the at least one attachment. | 8. A system, comprising: a network device comprising a first processor and configured to manage a messaging component for receiving and sending messages over a network; and a tagging component residing on another network device comprising a second processor, the tagging component operative to perform actions, including: receiving a message having at least one attachment from the messaging component; using a machine learning model to select at least one sentence from within the message to be relevant to the at least one attachment based on a set of predefined sentence level features; identifying from within the at least one relevant sentences a set of keywords further relevant to the at least one attachment; and associating at least one of the keywords in the set to the at least one attachment, such that the association is useable for at least one of indexing or searching of the at least one attachment. 12. The system of claim 8 , wherein the tagging component is configured to employ feedback about the set of keywords and to learn over time to predict at least one other keyword that is to be retained or deleted from the set of keywords. | 0.727856 |
8. The computer program product of claim 1 , wherein a plurality of converted character strings are generated by appending a plurality of characters corresponding to a plurality of inflectional forms thereto, respectively, where at least one character is appended to each inflectional form, with respect to the target character string of an inflectional word. | 8. The computer program product of claim 1 , wherein a plurality of converted character strings are generated by appending a plurality of characters corresponding to a plurality of inflectional forms thereto, respectively, where at least one character is appended to each inflectional form, with respect to the target character string of an inflectional word. 9. The computer program product of claim 8 , further comprising determining whether the converted character string has an attribute based on the target character string based on a frequency at which the converted character string matches at least one third text with which the attribute is associated; and wherein the retrieval condition of matching the target character string and not matching the converted character string is generated based on the converted character string not having the attribute. | 0.814065 |
1. A method comprising performing a machine-executed operation involving instructions for identifying a navigational query, wherein the machine-executed operation is at least one of: A) storing said instructions onto a volatile or non-volatile storage medium; and B)executing the instructions; wherein said instructions are instructions which, when executed by one or more processors, cause performance of: determining whether a query is a navigational query by receiving a set of query-URL pair-wise features based at least in part on said query in conjunction with an associated query result set; integrating subsets of said set of query-URL pair-wise features to generate a set of query-based features that are independent of any particular URL; automatically selecting, from said set of query-based features, a subset of most effective features for identifying navigational queries, wherein said selecting is based on a machine learning feature selection method; based on said subset of most effective features, using a machine learning classification method to determine whether said query is a navigational query. | 1. A method comprising performing a machine-executed operation involving instructions for identifying a navigational query, wherein the machine-executed operation is at least one of: A) storing said instructions onto a volatile or non-volatile storage medium; and B)executing the instructions; wherein said instructions are instructions which, when executed by one or more processors, cause performance of: determining whether a query is a navigational query by receiving a set of query-URL pair-wise features based at least in part on said query in conjunction with an associated query result set; integrating subsets of said set of query-URL pair-wise features to generate a set of query-based features that are independent of any particular URL; automatically selecting, from said set of query-based features, a subset of most effective features for identifying navigational queries, wherein said selecting is based on a machine learning feature selection method; based on said subset of most effective features, using a machine learning classification method to determine whether said query is a navigational query. 18. The method of claim 1 , wherein said machine learning classification method is a support vector machine method. | 0.776062 |
9. A system for identifying trends of fault occurrences in a manufacturing process with a Markov model, the system comprising: a plurality of modules wherein each module includes non-transitory computer-readable medium with an executable program stored thereon, the plurality of modules including: an input module configured to receive a plurality of data series and input parameters; a sort module configured to sort the plurality of data series to form a sorted plurality of data series, said data series including discrete data elements that identify the fault occurrences in the manufacturing process; a selection module configured to select data series from the sorted plurality of data series to form selected data series; a class development module configured to develop a plurality of classes from the selected data series and input parameters; and a binning and classification module configured to bin and classify the selected data series according to an input parameter and the plurality of classes, where the discrete data elements in each of the data series are classified into a particular bin depending on when they occurred, wherein the binning and classification module clusters the classified data series to iteratively arrange the data elements into clusters to meet a predetermined criteria, and wherein classifying the selected data series includes identifying the fault occurrences according to frequency of occurrence, mean time to repair and/or duration of downtime and selecting the most frequently occurring fault occurrences and/or the fault occurrences resulting in the longest downtime duration; a Markov model initialization module configured to initialize the Markov model for trend prediction including determining the number of known states in the Markov model based on the data series and associating a state of the Markov model for each class of data determined by the binned and classified data series; a Markov model training module configured to train the Markov model for trend prediction of the binned and classified data series to form a trained Markov model, said Markov model being trained to predict trends of the data series by determining the probability of states of the data as classified and binned and the probability of the transition of data from state to state where the state probabilities are calculated for the data series by evaluating a probability in a training window, wherein training the Markov model includes training the model to predict the frequency of occurrence, the mean time to repair and/or the downtime duration of the fault occurrences, using the model to predict frequency and/or duration of the fault occurrences during a testing period immediately succeeding a training period of the model, and evaluating the accuracy of the trend predictions by comparing the trend predictions during the testing period with actual data obtained during the testing period; an output module configured to output trend predictions upon deployment of the trained Markov model that identify predictions of fault occurrences that may occur during the manufacturing process; and updating the training of the model when new data is obtained during the manufacturing process. | 9. A system for identifying trends of fault occurrences in a manufacturing process with a Markov model, the system comprising: a plurality of modules wherein each module includes non-transitory computer-readable medium with an executable program stored thereon, the plurality of modules including: an input module configured to receive a plurality of data series and input parameters; a sort module configured to sort the plurality of data series to form a sorted plurality of data series, said data series including discrete data elements that identify the fault occurrences in the manufacturing process; a selection module configured to select data series from the sorted plurality of data series to form selected data series; a class development module configured to develop a plurality of classes from the selected data series and input parameters; and a binning and classification module configured to bin and classify the selected data series according to an input parameter and the plurality of classes, where the discrete data elements in each of the data series are classified into a particular bin depending on when they occurred, wherein the binning and classification module clusters the classified data series to iteratively arrange the data elements into clusters to meet a predetermined criteria, and wherein classifying the selected data series includes identifying the fault occurrences according to frequency of occurrence, mean time to repair and/or duration of downtime and selecting the most frequently occurring fault occurrences and/or the fault occurrences resulting in the longest downtime duration; a Markov model initialization module configured to initialize the Markov model for trend prediction including determining the number of known states in the Markov model based on the data series and associating a state of the Markov model for each class of data determined by the binned and classified data series; a Markov model training module configured to train the Markov model for trend prediction of the binned and classified data series to form a trained Markov model, said Markov model being trained to predict trends of the data series by determining the probability of states of the data as classified and binned and the probability of the transition of data from state to state where the state probabilities are calculated for the data series by evaluating a probability in a training window, wherein training the Markov model includes training the model to predict the frequency of occurrence, the mean time to repair and/or the downtime duration of the fault occurrences, using the model to predict frequency and/or duration of the fault occurrences during a testing period immediately succeeding a training period of the model, and evaluating the accuracy of the trend predictions by comparing the trend predictions during the testing period with actual data obtained during the testing period; an output module configured to output trend predictions upon deployment of the trained Markov model that identify predictions of fault occurrences that may occur during the manufacturing process; and updating the training of the model when new data is obtained during the manufacturing process. 12. The system of claim 9 , wherein: the training module applies a metric to the Markov model for determining goodness of the Markov model; and training the Markov model for trend prediction comprises adjusting the state probabilities and transition probabilities to obtain substantially optimal performance of the Markov model according to the metric. | 0.5 |
8. A system for multimedia summary generation, wherein the system comprises: a processor containing a plurality of modules, including: a transmitter/receiver module for transmitting/receiving data; a multimedia source capturing module for capturing multimedia information from the multimedia source, wherein the multimedia information comprises at least a video clip or a picture; a multimedia source processing module coupled to the multimedia source capturing module for receiving the multimedia information captured by the multimedia source capturing module and for processing the video clip and the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; a multimedia source summary generation module coupled to the multimedia source processing module for receiving the multimedia summary candidate to generate a multimedia summary list, wherein the multimedia source summary generation module checks whether the multimedia summary list contains a predetermined threshold, the multimedia source summary generation module outputs the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, the multimedia source summary generation module checks whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined, the multimedia source summary generation module joins the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold, the multimedia source summary generation module ignores the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold, and the multimedia source summary generation module combines the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; the multimedia source summary generation module sends message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group; wherein the modules are operated under the control of the processor; wherein the predetermined threshold of the multimedia source summary generation module comprises at least a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate, or a combination therefore. | 8. A system for multimedia summary generation, wherein the system comprises: a processor containing a plurality of modules, including: a transmitter/receiver module for transmitting/receiving data; a multimedia source capturing module for capturing multimedia information from the multimedia source, wherein the multimedia information comprises at least a video clip or a picture; a multimedia source processing module coupled to the multimedia source capturing module for receiving the multimedia information captured by the multimedia source capturing module and for processing the video clip and the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; a multimedia source summary generation module coupled to the multimedia source processing module for receiving the multimedia summary candidate to generate a multimedia summary list, wherein the multimedia source summary generation module checks whether the multimedia summary list contains a predetermined threshold, the multimedia source summary generation module outputs the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, the multimedia source summary generation module checks whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined, the multimedia source summary generation module joins the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold, the multimedia source summary generation module ignores the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold, and the multimedia source summary generation module combines the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; the multimedia source summary generation module sends message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group; wherein the modules are operated under the control of the processor; wherein the predetermined threshold of the multimedia source summary generation module comprises at least a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate, or a combination therefore. 12. The system according to claim 8 , wherein the multimedia source processing module further comprises executing a step of multimedia information arrangement, the executing a step of multimedia information arrangement comprising: searching a relevant multimedia source from the multimedia information; establishing a linking relationship between the multimedia information and the searched relevant multimedia source; and playing the multimedia information. | 0.5 |
1. A computer-implemented method, comprising: generating a set of seed rules comprising: one or more rules resulting from one or more previously performed machine learning operations that were previously performed in regard to a set of item description entries, and one or more randomly or pseudo-randomly generated rules; performing one or more machine learning operations on the set of seed rules to generate a set of duplicate detection rules for determining whether a given pair of item description entries is a duplicate pair, wherein a given duplicate pair represents different item description entries that describe a common item, wherein said performing the one or more machine learning operations on the set of seed rules is performed in regard to another set of item description entries, wherein the other set of item description entries includes one or more differences from the set of item description entries in regard to which the one or more previously performed machine learning operations were previously performed; and applying the set of duplicate detection rules to multiple item description entries to identify at least one duplicate pair of item description entries. | 1. A computer-implemented method, comprising: generating a set of seed rules comprising: one or more rules resulting from one or more previously performed machine learning operations that were previously performed in regard to a set of item description entries, and one or more randomly or pseudo-randomly generated rules; performing one or more machine learning operations on the set of seed rules to generate a set of duplicate detection rules for determining whether a given pair of item description entries is a duplicate pair, wherein a given duplicate pair represents different item description entries that describe a common item, wherein said performing the one or more machine learning operations on the set of seed rules is performed in regard to another set of item description entries, wherein the other set of item description entries includes one or more differences from the set of item description entries in regard to which the one or more previously performed machine learning operations were previously performed; and applying the set of duplicate detection rules to multiple item description entries to identify at least one duplicate pair of item description entries. 3. The computer-implemented method of claim 1 , wherein performing said one or more machine learning operations includes performing genetic algorithm (GA) operations including one or more of: a mutation operation or a crossover operation. | 0.704282 |
1. A language understanding device comprising: a language understanding model storing unit configured to store, as a language understanding model, word transition data, filler transition data and concept weighting data, said word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, filler transition data including pre-transition states, fillers matching an arbitrary word, filler weight information, and post-transition states, and said concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates based on words included in a word sequence being input which is obtained by a speech recognition process and present states, said understanding result candidates including the predefined outputs, and in accordance with the word transition data read out from the language understanding model storing unit, to accumulate word weights so as to obtain a cumulative word weight as a numeric value for each of the understanding result candidates, and to sequentially perform state transition operations by which transitions to the post-transition states are carried out; the finite state transducer processing unit is further configured to accumulate filler weights in accordance with the filler transition data read out from the language understanding model storing unit so as to obtain a cumulative filler weight as a numeric value for each of the understanding result candidates, and to perform the state transition operations by which transition to the post-transition states are carried out; a concept weighting processing unit configured to accumulate concept weights, which correspond to the concepts included in the understanding result candidates output from the finite state transducer processing unit, in accordance with the concept weighting data read out from the language understanding model storing unit so as to obtain a cumulative concept weight as a numeric value for each of the understanding result candidates; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates based on the cumulative word weight, the cumulative filler weight and the cumulative concept weight for each understanding result candidate, wherein the understanding result determination unit is configured to determine the understanding result as the understanding result candidate having a highest value for a summed cumulative word weight, cumulative filler weight and cumulative concept weight. | 1. A language understanding device comprising: a language understanding model storing unit configured to store, as a language understanding model, word transition data, filler transition data and concept weighting data, said word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, filler transition data including pre-transition states, fillers matching an arbitrary word, filler weight information, and post-transition states, and said concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates based on words included in a word sequence being input which is obtained by a speech recognition process and present states, said understanding result candidates including the predefined outputs, and in accordance with the word transition data read out from the language understanding model storing unit, to accumulate word weights so as to obtain a cumulative word weight as a numeric value for each of the understanding result candidates, and to sequentially perform state transition operations by which transitions to the post-transition states are carried out; the finite state transducer processing unit is further configured to accumulate filler weights in accordance with the filler transition data read out from the language understanding model storing unit so as to obtain a cumulative filler weight as a numeric value for each of the understanding result candidates, and to perform the state transition operations by which transition to the post-transition states are carried out; a concept weighting processing unit configured to accumulate concept weights, which correspond to the concepts included in the understanding result candidates output from the finite state transducer processing unit, in accordance with the concept weighting data read out from the language understanding model storing unit so as to obtain a cumulative concept weight as a numeric value for each of the understanding result candidates; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates based on the cumulative word weight, the cumulative filler weight and the cumulative concept weight for each understanding result candidate, wherein the understanding result determination unit is configured to determine the understanding result as the understanding result candidate having a highest value for a summed cumulative word weight, cumulative filler weight and cumulative concept weight. 3. The language understanding device according to claim 1 , wherein the word sequence being input includes N word-sequences, where N is a natural number equal to or greater than 2, the finite state transducer processing unit is further configured to output the understanding result candidates for each of the N word-sequences by performing the state transition operations for each of the N word-sequences, and the understanding result determination unit is further configured to determine the understanding result from all of the understanding result candidates corresponding to the N word-sequences. | 0.578541 |
11. The method of claim 10 , further comprising: dividing the template-typicality scores of each of the typicality proto-groups into Q number of template-typicality ranges, each of the template-typicality ranges corresponding to one proto-corpus of the set of proto-corpuses, each of templates in the one proto-corpus having a template-typicality score within a template-typicality range corresponding to the one proto-corpus, each proto-corpus of the set of the proto-corpuses having about a same number of templates as other ones of the set of proto-corpuses. | 11. The method of claim 10 , further comprising: dividing the template-typicality scores of each of the typicality proto-groups into Q number of template-typicality ranges, each of the template-typicality ranges corresponding to one proto-corpus of the set of proto-corpuses, each of templates in the one proto-corpus having a template-typicality score within a template-typicality range corresponding to the one proto-corpus, each proto-corpus of the set of the proto-corpuses having about a same number of templates as other ones of the set of proto-corpuses. 12. The method of claim 11 , further comprising: performing the matching operation between the probe and prototype templates of each of the typicality proto-groups to generate probe-match scores; averaging the probe-match scores to generate a probe-typicality score; selecting a proto-corpus from each set of proto-corpuses based on the probe-typicality score corresponding to the set of proto-corpuses; and placing templates that are in all selected proto-corpuses to form the search corpus. | 0.807011 |
6. A method comprising: under control of one or more processors configured with executable instructions, receiving a first location associated with a portion of a first version of a content item, the portion of the first version being in a first language; determining a second location associated with a portion of a second version of the content item, the portion of the second version being in a second language, wherein: the second language is different from the first language, and content of the portion of the second version corresponds, at least in part, to content of the portion of the first version; returning the second location; presenting a first amount of the content of the portion of the first version in a first area; presenting a first amount of the content of the portion of the second version in a second area; determining a second amount of the content of the portion of the first version to present within the first area; determining a second amount of the content of the portion of the second version to present based at least in part on associating the second amount of the content of the portion of the second version with the second amount of the content of the portion of the first version; and adjusting a size of the second area based at least in part on the second amount of the content of the portion of the second version. | 6. A method comprising: under control of one or more processors configured with executable instructions, receiving a first location associated with a portion of a first version of a content item, the portion of the first version being in a first language; determining a second location associated with a portion of a second version of the content item, the portion of the second version being in a second language, wherein: the second language is different from the first language, and content of the portion of the second version corresponds, at least in part, to content of the portion of the first version; returning the second location; presenting a first amount of the content of the portion of the first version in a first area; presenting a first amount of the content of the portion of the second version in a second area; determining a second amount of the content of the portion of the first version to present within the first area; determining a second amount of the content of the portion of the second version to present based at least in part on associating the second amount of the content of the portion of the second version with the second amount of the content of the portion of the first version; and adjusting a size of the second area based at least in part on the second amount of the content of the portion of the second version. 19. The method of claim 6 , further comprising adjusting a size of the first area based at least in part on adjusting the size of the second area. | 0.750188 |
1. A method of communicating a modular document from a first electronic device to a second electronic device, comprising: determining, by the first electronic device, which one or more component documents of the modular document are already available at the second electronic device, wherein the modular document is composed of plural component documents; and creating, by the first electronic device, a package that includes the modular document and a subset of the plural component documents of the modular document, wherein the subset of the plural component documents is other than the one or more component documents already available at the second electronic device, wherein the modular document in the package includes references to the plural component documents, and wherein the first electronic device does not include in the package the one or more component documents determined by the first electronic device to be already available at the second electronic device; and sending, by the first electronic device to the second electronic device, the package. | 1. A method of communicating a modular document from a first electronic device to a second electronic device, comprising: determining, by the first electronic device, which one or more component documents of the modular document are already available at the second electronic device, wherein the modular document is composed of plural component documents; and creating, by the first electronic device, a package that includes the modular document and a subset of the plural component documents of the modular document, wherein the subset of the plural component documents is other than the one or more component documents already available at the second electronic device, wherein the modular document in the package includes references to the plural component documents, and wherein the first electronic device does not include in the package the one or more component documents determined by the first electronic device to be already available at the second electronic device; and sending, by the first electronic device to the second electronic device, the package. 6. The method of claim 1 , wherein the modular document includes a primary document that has inclusion references to the plural component documents, the inclusion references to the plural component documents including reference to the one or more component documents determined not included in the package. | 0.62699 |
8. The system of claim 7 , wherein the workflow instance is an instance of a workflow definition comprising a plurality of possible paths of execution, and the test document is associated with the workflow definition. | 8. The system of claim 7 , wherein the workflow instance is an instance of a workflow definition comprising a plurality of possible paths of execution, and the test document is associated with the workflow definition. 9. The system of claim 8 , further comprising logic that generates an additional test scenario that is inserted into the test document based at least in part upon a log of a plurality of prior instances of the workflow definition, the plurality of prior instances representing a subset of the plurality of possible paths of execution of the workflow definition. | 0.905127 |
1. A system for increasing accuracy of computer speech recognition comprising: a dynamic grammar builder computing device comprising one or more processing units and one or more computer-readable media comprising computer-executable instructions which, when executed by the one or more processing units, cause the dynamic grammar builder computing device to: obtain social network data occurring within a threshold timespan of a broadcast of media content; identify named entities from the obtained social network data that are trending within the obtained social network data; rank the identified named entities based upon the trending; and build a dynamic grammar comprising at least some of the named entities based upon the ranking; and a speech recognition computing device comprising one or more processing units and one or more computer-readable media comprising computer-executable instructions which, when executed by the one or more processing units, cause the speech recognition computing device to: perform speech recognition of spoken words, spoken by the broadcast of the media content, utilizing the dynamic grammar to create closed caption text for the broadcast of the media content. | 1. A system for increasing accuracy of computer speech recognition comprising: a dynamic grammar builder computing device comprising one or more processing units and one or more computer-readable media comprising computer-executable instructions which, when executed by the one or more processing units, cause the dynamic grammar builder computing device to: obtain social network data occurring within a threshold timespan of a broadcast of media content; identify named entities from the obtained social network data that are trending within the obtained social network data; rank the identified named entities based upon the trending; and build a dynamic grammar comprising at least some of the named entities based upon the ranking; and a speech recognition computing device comprising one or more processing units and one or more computer-readable media comprising computer-executable instructions which, when executed by the one or more processing units, cause the speech recognition computing device to: perform speech recognition of spoken words, spoken by the broadcast of the media content, utilizing the dynamic grammar to create closed caption text for the broadcast of the media content. 5. The system of claim 1 , wherein the ranking comprises responsive to a refresh timer expiring, re-ranking the named entities based upon the trending within updated social network data. | 0.699707 |
1. A method for multimedia summary generation adapted to a multimedia system, wherein the method comprises following steps: capturing a multimedia information from a multimedia source, wherein the multimedia information comprises at least a video clip or a picture; processing the video clip or the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; generating a multimedia summary list by checking whether a threshold is predetermined; outputting the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, checking whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined; joining the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold; ignoring the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold; combining the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; and sending message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group, wherein the predetermined threshold is realizable at least by a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate or a combination thereof. | 1. A method for multimedia summary generation adapted to a multimedia system, wherein the method comprises following steps: capturing a multimedia information from a multimedia source, wherein the multimedia information comprises at least a video clip or a picture; processing the video clip or the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; generating a multimedia summary list by checking whether a threshold is predetermined; outputting the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, checking whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined; joining the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold; ignoring the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold; combining the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; and sending message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group, wherein the predetermined threshold is realizable at least by a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate or a combination thereof. 5. The method according to claim 1 , further comprising a multimedia information arrangement step, the multimedia information arrangement step comprising: searching a relevant multimedia source from the multimedia information; establishing a linking relationship between the multimedia information and the searched relevant multimedia source; and playing the multimedia information. | 0.659822 |
16. The method of claim 15 , wherein the step of generating characteristic coefficients comprises, for each coefficient: forming a vector representing probabilities of the parts; forming a matrix B with copies of the vector as its columns; and computing the determinant of the Gram matrix given by |B T B| to generate each coefficient. | 16. The method of claim 15 , wherein the step of generating characteristic coefficients comprises, for each coefficient: forming a vector representing probabilities of the parts; forming a matrix B with copies of the vector as its columns; and computing the determinant of the Gram matrix given by |B T B| to generate each coefficient. 17. The method of claim 16 , wherein the step of generating characteristic coefficients comprises computing a recursion such that each coefficient is based on those coefficients already computed. | 0.852659 |
1. An image processing apparatus comprising: an image acquisition unit that acquires an input image that is to be subjected to processing; a foreground map generation unit that generates a foreground map, which indicates a foreground region and a background region in the input image, based on the input image; a learning sample extraction unit that extracts data of a positive learning sample from the foreground region in the input image and extracts data of a negative learning sample from the background region in the input image, based on the foreground map; a classifier learning unit that performs learning of a plurality of classifiers using the positive and negative learning samples extracted from the input image; a strong classifier generation unit that generates a strong classifier by combining the plurality of learned classifiers; and a saliency map generation unit that generates a final saliency map of the input image using the strong classifier. | 1. An image processing apparatus comprising: an image acquisition unit that acquires an input image that is to be subjected to processing; a foreground map generation unit that generates a foreground map, which indicates a foreground region and a background region in the input image, based on the input image; a learning sample extraction unit that extracts data of a positive learning sample from the foreground region in the input image and extracts data of a negative learning sample from the background region in the input image, based on the foreground map; a classifier learning unit that performs learning of a plurality of classifiers using the positive and negative learning samples extracted from the input image; a strong classifier generation unit that generates a strong classifier by combining the plurality of learned classifiers; and a saliency map generation unit that generates a final saliency map of the input image using the strong classifier. 2. The image processing apparatus according to claim 1 , wherein the foreground map is a map having values indicating foreground-likelihood for each pixel or each super-pixel of the image, and wherein the learning sample extraction unit extracts a pixel or a super-pixel having a value indicating foreground-likelihood that is greater than a first threshold value as a positive learning sample, and extracts a pixel or a super-pixel having a value indicating foreground-likelihood that is less than a second threshold value as a negative learning sample. | 0.5 |
1. A method of defining a common interactions protocol between two entities, the method comprising: the method performed by a communication server arranged for: converting syntactic specifications of multiple documents to be passed between the entities, into a skeleton semantic web ontology comprising a set of classes; deriving for each entity a respective set of constraints including semantic constraints established by the entity on aspects of the classes of the skeleton ontology; calculating the union of the two sets of constraints; determining, using a constraint resolver that comprises a description logic reasoner, whether the union is satisfiable, and: where the union is satisfiable, deriving from the intersection of the two sets of constraints a restricted document specification that is compatible with the constraint sets of both entities; and where the union is not satisfiable, indicating where any incompatibility lies. | 1. A method of defining a common interactions protocol between two entities, the method comprising: the method performed by a communication server arranged for: converting syntactic specifications of multiple documents to be passed between the entities, into a skeleton semantic web ontology comprising a set of classes; deriving for each entity a respective set of constraints including semantic constraints established by the entity on aspects of the classes of the skeleton ontology; calculating the union of the two sets of constraints; determining, using a constraint resolver that comprises a description logic reasoner, whether the union is satisfiable, and: where the union is satisfiable, deriving from the intersection of the two sets of constraints a restricted document specification that is compatible with the constraint sets of both entities; and where the union is not satisfiable, indicating where any incompatibility lies. 4. The method according to claim 1 , wherein the communication server is further arranged for: pre-specifying semantic constraints and associating them with deployment contexts; the deriving of the set of constraints for that entity comprising defining a particular deployment context for the common interactions protocol, and determining which of the pre-specified semantic constraints are applicable to said particular deployment context. | 0.5 |
7. A method, including comprising: accessing, by a context module including at least one processor, data identifying a context in relation to a category of merchant offerings in a network-based marketplace, the context being associated with a user of the network; processing information from a plurality of other users of the network regarding the category of merchant offerings to determine attributes relevant to the context; receiving input from the user including a selection of at least one of the attributes; and generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute and according to one of one or more ratings associated with buyers or sellers of products or services included in the result data. | 7. A method, including comprising: accessing, by a context module including at least one processor, data identifying a context in relation to a category of merchant offerings in a network-based marketplace, the context being associated with a user of the network; processing information from a plurality of other users of the network regarding the category of merchant offerings to determine attributes relevant to the context; receiving input from the user including a selection of at least one of the attributes; and generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute and according to one of one or more ratings associated with buyers or sellers of products or services included in the result data. 11. The method of claim 7 , further comprising: selectively updating the result data based on receiving new data associated with the context. | 0.814136 |
1. A computer-implemented method of generating graphical user analysis interfaces, the method comprising: at an analytics engine configured to analyze a set of items based on data models and processing models: receiving, at a first time, a first indication that first client data is available for use by the analytics engine, wherein a first portion of the first client data is stored on a first data storage device, wherein a second portion of the first client data is stored on a second data storage device that is distinct from the first data storage device, and wherein the analytics engine is configured to analyze the first client data using the set of items; populating columns of a plurality of fact tables with the first client data; populating and storing a table-info table to indicate which columns in each of the plurality of fact tables are populated with the first client data; evaluating a plurality of content measures based on the populated columns of the plurality of fact tables, the table-info table, and at least one of a role or a security access level of a user to determine and store a set of computable content measures that are supported by the first client data; identifying supported items of the set of items based on the stored set of computable content measures; sending first graphical user interface (GUI) data to a client instance, wherein display of the first GUI data shows the supported items and excludes unsupported items; receiving, at a second time, a second indication that a portion of the first client data has become unavailable; determining that at least one of the supported items relies on the portion of the first client data; sending second GUI data to the client instance, wherein display of the second GUI data excludes the at least one of the supported items; receiving, from the client instance, a query that requests values spanning both the first portion and the second portion; and responsive to receiving the query, dividing the query into a plurality of data requests, the plurality of data requests including a first request with respect to the first portion and a second request with respect to the second portion. | 1. A computer-implemented method of generating graphical user analysis interfaces, the method comprising: at an analytics engine configured to analyze a set of items based on data models and processing models: receiving, at a first time, a first indication that first client data is available for use by the analytics engine, wherein a first portion of the first client data is stored on a first data storage device, wherein a second portion of the first client data is stored on a second data storage device that is distinct from the first data storage device, and wherein the analytics engine is configured to analyze the first client data using the set of items; populating columns of a plurality of fact tables with the first client data; populating and storing a table-info table to indicate which columns in each of the plurality of fact tables are populated with the first client data; evaluating a plurality of content measures based on the populated columns of the plurality of fact tables, the table-info table, and at least one of a role or a security access level of a user to determine and store a set of computable content measures that are supported by the first client data; identifying supported items of the set of items based on the stored set of computable content measures; sending first graphical user interface (GUI) data to a client instance, wherein display of the first GUI data shows the supported items and excludes unsupported items; receiving, at a second time, a second indication that a portion of the first client data has become unavailable; determining that at least one of the supported items relies on the portion of the first client data; sending second GUI data to the client instance, wherein display of the second GUI data excludes the at least one of the supported items; receiving, from the client instance, a query that requests values spanning both the first portion and the second portion; and responsive to receiving the query, dividing the query into a plurality of data requests, the plurality of data requests including a first request with respect to the first portion and a second request with respect to the second portion. 8. The method of claim 1 , wherein the stored set of computable content measures is reusable to identify the supported items while the first client data remains available and while the at least one of the role or the security access level of the user is unchanged. | 0.635447 |
1. A computer-implemented method of ensuring selective disclosure of sensitive data: a computer storing in a memory one or more sets of truth data items, and at least one policy comprised of policy variables indicating which type of data items are sensitive, which type of data item is disclosable, validity conditions for a candidate disclosure dataset to be believable by a recipient, and sufficiency conditions specifying an extent of variability necessary among data objects in a disclosure candidate dataset to protect the sensitive data; the computer performing the steps of: producing a collection of synthetic dataset disclosure possibilities meeting the validity conditions; producing one or more associations between the policy variables and each synthetic dataset disclosure possibility meeting the validity conditions, and each of the one or more truth data sets; generating at least one candidate disclosure dataset from the collection of synthetic datasets disclosure possibilities and the truth data items comprising at least one of a synthetic dataset and a truth dataset, wherein respective values of the collection of synthetic dataset disclosure possibilities vary by at least the extent specified in the policy; and iteratively repeating the producing steps and the generating step until the associations corresponding to the at least one candidate disclosure dataset meet the sufficiency conditions of the at least one policy, and each of the at least one candidate disclosure dataset meets the validity conditions of the at least one policy; and performing at least one of the following actions: generating a certificate indicating that the at least one candidate disclosure dataset complies with the at least one policy; automatically providing the at least one candidate disclosure dataset to a recipient; or requesting approval from a holder of the sensitive data to disclose the at least one candidate disclosure dataset. | 1. A computer-implemented method of ensuring selective disclosure of sensitive data: a computer storing in a memory one or more sets of truth data items, and at least one policy comprised of policy variables indicating which type of data items are sensitive, which type of data item is disclosable, validity conditions for a candidate disclosure dataset to be believable by a recipient, and sufficiency conditions specifying an extent of variability necessary among data objects in a disclosure candidate dataset to protect the sensitive data; the computer performing the steps of: producing a collection of synthetic dataset disclosure possibilities meeting the validity conditions; producing one or more associations between the policy variables and each synthetic dataset disclosure possibility meeting the validity conditions, and each of the one or more truth data sets; generating at least one candidate disclosure dataset from the collection of synthetic datasets disclosure possibilities and the truth data items comprising at least one of a synthetic dataset and a truth dataset, wherein respective values of the collection of synthetic dataset disclosure possibilities vary by at least the extent specified in the policy; and iteratively repeating the producing steps and the generating step until the associations corresponding to the at least one candidate disclosure dataset meet the sufficiency conditions of the at least one policy, and each of the at least one candidate disclosure dataset meets the validity conditions of the at least one policy; and performing at least one of the following actions: generating a certificate indicating that the at least one candidate disclosure dataset complies with the at least one policy; automatically providing the at least one candidate disclosure dataset to a recipient; or requesting approval from a holder of the sensitive data to disclose the at least one candidate disclosure dataset. 2. The method of claim 1 , wherein if the sufficiency conditions or validity conditions are not met, the producing steps comprise producing an additional synthetic dataset disclosure possibility and corresponding association, and adding them to the at least one candidate disclosure dataset. | 0.5 |
12. A computer program product for partitioning a video sequence, comprising: a non-transitory computer readable storage medium; first program instructions to divide a video sequence into a plurality of segments; second program instructions to generate a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; third program instructions to select a plurality of keywords from the plurality of words in the transcript; fourth program instructions to select a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; fifth program instructions to determine a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; sixth program instructions to select a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; seventh program instructions to form a partition of the video sequence from the group of segments; and wherein the first, second, third, fourth, fifth, sixth, and seventh program instructions are stored on the non-transitory computer readable storage medium, wherein the second program instructions comprise program instructions to: generate the transcript of speech content of the video sequence from audio content of the video sequence using automatic speech recognition; determine whether the transcript generated from the audio content is satisfactory; determine whether the video sequence has closed caption, responsive to a determination that the transcript generated from the audio content is not satisfactory; and generate the transcript from the closed caption, responsive to a determination that the video sequence has closed caption. | 12. A computer program product for partitioning a video sequence, comprising: a non-transitory computer readable storage medium; first program instructions to divide a video sequence into a plurality of segments; second program instructions to generate a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; third program instructions to select a plurality of keywords from the plurality of words in the transcript; fourth program instructions to select a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; fifth program instructions to determine a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; sixth program instructions to select a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; seventh program instructions to form a partition of the video sequence from the group of segments; and wherein the first, second, third, fourth, fifth, sixth, and seventh program instructions are stored on the non-transitory computer readable storage medium, wherein the second program instructions comprise program instructions to: generate the transcript of speech content of the video sequence from audio content of the video sequence using automatic speech recognition; determine whether the transcript generated from the audio content is satisfactory; determine whether the video sequence has closed caption, responsive to a determination that the transcript generated from the audio content is not satisfactory; and generate the transcript from the closed caption, responsive to a determination that the video sequence has closed caption. 15. The computer program product of claim 12 , further comprising: eighth program instructions to generate a sound label for each of the plurality of segments, wherein the sound label indicates a class of sound in audio content of a corresponding segment; ninth program instructions to generate a visual label for each of the plurality of segments, wherein the visual label indicates a class of visual content of the corresponding segment; tenth program instructions to select a one of the plurality of segments as a boundary for the partition using a one of the sound label or the visual label for the selected one of the plurality of segments; and wherein the eighth, ninth, and tenth program instructions are stored on the non-transitory computer readable storage medium. | 0.5 |
8. An apparatus for generating a unified modeling language (UML) activity diagram of a UML task object, the apparatus comprising: a processor that functions as: a class object modification unit that receives a command to modify a node of a UML class diagram of the UML task object, the UML class diagram defining at least one subtask node that is associated with the UML task object, the at least one subtask node including the node, and the node defining a set of steps performed by a subtask of the node; and a class diagram modification unit that automatically generates the UML activity diagram to selectively include the node in the UML activity diagram or selectively omit the node from the UML activity diagram, based on the command, the UML activity diagram defining a subset of a complete ordered set of a plurality of steps, subtasks, decision blocks, and transitions between the steps, subtasks, and decision blocks performed by the UML task object, wherein the command to modify the node of the class diagram indicates at least one of to include a first node to the class diagram and to omit a second node from the class diagram, wherein the command indicates to include the first node to the class diagram, and wherein the generating comprises including the first node in the generated UML activity diagram. | 8. An apparatus for generating a unified modeling language (UML) activity diagram of a UML task object, the apparatus comprising: a processor that functions as: a class object modification unit that receives a command to modify a node of a UML class diagram of the UML task object, the UML class diagram defining at least one subtask node that is associated with the UML task object, the at least one subtask node including the node, and the node defining a set of steps performed by a subtask of the node; and a class diagram modification unit that automatically generates the UML activity diagram to selectively include the node in the UML activity diagram or selectively omit the node from the UML activity diagram, based on the command, the UML activity diagram defining a subset of a complete ordered set of a plurality of steps, subtasks, decision blocks, and transitions between the steps, subtasks, and decision blocks performed by the UML task object, wherein the command to modify the node of the class diagram indicates at least one of to include a first node to the class diagram and to omit a second node from the class diagram, wherein the command indicates to include the first node to the class diagram, and wherein the generating comprises including the first node in the generated UML activity diagram. 9. The apparatus according to claim 8 , wherein the command indicates to omit the second node from the class diagram, and wherein the generating comprises omitting the second node from the class diagram. | 0.591564 |
30. The system of claim 29 , wherein: the plurality of machine translation resource servers further comprise at least one machine translation resource server which serves the other machine translation resource data. | 30. The system of claim 29 , wherein: the plurality of machine translation resource servers further comprise at least one machine translation resource server which serves the other machine translation resource data. 31. The system of claim 30 , wherein: the machine translation resource server which serves the other machine translation resource data stores a second, different language model for the target language. | 0.960042 |
1. A method of providing an answer keyword, by a device having a processor, to a user terminal, the method comprising: obtaining at least one of a search word history comprising a first inquiry search word of a certain domain pre-received from first user terminals, and webpage information selected by the first user terminals from a search result according to the search word history; extracting answer candidate keywords regarding the first inquiry search word from at least one of the search word history and the webpage information based on keyword lists of the certain domain; calculating a relation value between the first inquiry search word and each of the extracted answer candidate keywords; and when the first inquiry search word is received from a second user terminal, transmitting answer keywords for the first inquiry search word, which are selected from the answer candidate keywords based on the relation value, to the second user terminal. | 1. A method of providing an answer keyword, by a device having a processor, to a user terminal, the method comprising: obtaining at least one of a search word history comprising a first inquiry search word of a certain domain pre-received from first user terminals, and webpage information selected by the first user terminals from a search result according to the search word history; extracting answer candidate keywords regarding the first inquiry search word from at least one of the search word history and the webpage information based on keyword lists of the certain domain; calculating a relation value between the first inquiry search word and each of the extracted answer candidate keywords; and when the first inquiry search word is received from a second user terminal, transmitting answer keywords for the first inquiry search word, which are selected from the answer candidate keywords based on the relation value, to the second user terminal. 5. The method of claim 1 , wherein the calculating of the relation value comprises: calculating a first sub-relation value between the first inquiry search word and the answer candidate keywords based on a frequency of the answer candidate keywords being included in the search word history; calculating a second sub-relation value between the first inquiry search word and the answer candidate keywords based on a frequency of the answer candidate keywords being included in the webpage information; and calculating the relation value through linear combination of the first sub-relation value and the second sub-relation value. | 0.662759 |
1. A process for processing markup language documents relating to a news story, comprising the steps of: reading an input file having a first file format including a plurality of elements, the input file further including at least one of: timing information for representing distribution timing of the news story; and synchronization information for synchronizing a distribution of one of the plurality of elements with a distribution of another of the plurality of elements; the input file further including news story information for representing the news story; and verifying the first file format of the input file based on a document type definition defining a news story markup language. | 1. A process for processing markup language documents relating to a news story, comprising the steps of: reading an input file having a first file format including a plurality of elements, the input file further including at least one of: timing information for representing distribution timing of the news story; and synchronization information for synchronizing a distribution of one of the plurality of elements with a distribution of another of the plurality of elements; the input file further including news story information for representing the news story; and verifying the first file format of the input file based on a document type definition defining a news story markup language. 6. The process of claim 1, further comprising a step of importing an import file having a file format different than the first and second file formats to produce an imported file having a format according to the document type definition. | 0.622047 |
29. A storage for holding computer-executable instructions, the instructions comprising instructions for: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model in the graphical modeling environment to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment. | 29. A storage for holding computer-executable instructions, the instructions comprising instructions for: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model in the graphical modeling environment to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment. 33. The storage of claim 29 , wherein the instructions for applying the coding standard to the simulatable graphical model comprise instructions for: applying the coding standard to text-based code embedded in the simulatable graphical model in the graphical modeling environment. | 0.590607 |
14. The system of claim 10 , where the purchase decision gating factors for each candidate recommendation comprise a relevance measure, an expected exposure measure and an expected clarity measure. | 14. The system of claim 10 , where the purchase decision gating factors for each candidate recommendation comprise a relevance measure, an expected exposure measure and an expected clarity measure. 15. The system of claim 14 , where the purchase decision gating factors for each candidate recommendation further comprise a post-recommendation exposure measure and a post-recommendation clarity measure. | 0.939741 |
3. A computer system to select images for a markup language document, the computer system comprising: a processing unit; a memory coupled to the processing unit through a system bus; a computer-readable storage medium coupled to the processing unit through the system bus, and an instruction embedded in the markup language document in the memory to cause the processing unit to execute a utility program from the computer-readable storage medium, wherein the utility program causes the processing unit to: determine a number of images to display in the markup language document; obtain a set of random numbers, the set of random numbers containing a plurality of random numbers, a number of the plurality of random numbers being equal to the determined number of images; retrieve images from a group of images using the set of random numbers, each retrieved image being associated with an item represented in that retrieved image; determine a location in the markup language document for each of the retrieved images from an instruction embedded in the markup language document; and place the retrieved images in the markup language document, wherein the retrieved images are placed in the locations defined in the instruction. | 3. A computer system to select images for a markup language document, the computer system comprising: a processing unit; a memory coupled to the processing unit through a system bus; a computer-readable storage medium coupled to the processing unit through the system bus, and an instruction embedded in the markup language document in the memory to cause the processing unit to execute a utility program from the computer-readable storage medium, wherein the utility program causes the processing unit to: determine a number of images to display in the markup language document; obtain a set of random numbers, the set of random numbers containing a plurality of random numbers, a number of the plurality of random numbers being equal to the determined number of images; retrieve images from a group of images using the set of random numbers, each retrieved image being associated with an item represented in that retrieved image; determine a location in the markup language document for each of the retrieved images from an instruction embedded in the markup language document; and place the retrieved images in the markup language document, wherein the retrieved images are placed in the locations defined in the instruction. 5. The computer system of claim 3 , wherein the computer-readable storage medium further comprises an administration program that causes the processing unit to create a group of images from which to select the number of images. | 0.5 |
47. A system comprising: a user interface configured to enable the user to select and provide content items and to select privacy settings and/or sharing and publication setting for each content item and/or different types of contents selected and provided via the interface to control interactions of other users of the network related or connected to the user with each content item and/or multiple different types of content, a content repository for receiving a content item and/or one or more types with an associated privacy setting and/or sharing and publication setting identifying one or more connections and/or set of users and/or determined users and/or subscribers allowed to access the content item and/or one or more types of content, a content publishing module for publishing the content item and/or one or more types of content into a communication channel of the network and providing or presenting or publishing the content item to one or more connections and/or set of users and/or determined users and/or subscribers via the communication channel, wherein the content item is presented or provided or published based on the privacy setting and/or sharing and publication setting associated with the content item and/or one or more types of content, and enable receivers including one or more connections and/or set of users and/or determined users and/or subscribers to manage and/or access the content item and/or one or more types of content, where accessibility to the one or more connections and/or set of users and/or determined users and/or subscribers is determined by the privacy settings and/or sharing and publication setting selected by the user; and responsive to receiving a privacy setting and sharing and publication setting to be associated with the content item from locking the content item from being published a communication channel accessible to one or more connections, exclude the content item from the communication channel accessible to the one or more connections. | 47. A system comprising: a user interface configured to enable the user to select and provide content items and to select privacy settings and/or sharing and publication setting for each content item and/or different types of contents selected and provided via the interface to control interactions of other users of the network related or connected to the user with each content item and/or multiple different types of content, a content repository for receiving a content item and/or one or more types with an associated privacy setting and/or sharing and publication setting identifying one or more connections and/or set of users and/or determined users and/or subscribers allowed to access the content item and/or one or more types of content, a content publishing module for publishing the content item and/or one or more types of content into a communication channel of the network and providing or presenting or publishing the content item to one or more connections and/or set of users and/or determined users and/or subscribers via the communication channel, wherein the content item is presented or provided or published based on the privacy setting and/or sharing and publication setting associated with the content item and/or one or more types of content, and enable receivers including one or more connections and/or set of users and/or determined users and/or subscribers to manage and/or access the content item and/or one or more types of content, where accessibility to the one or more connections and/or set of users and/or determined users and/or subscribers is determined by the privacy settings and/or sharing and publication setting selected by the user; and responsive to receiving a privacy setting and sharing and publication setting to be associated with the content item from locking the content item from being published a communication channel accessible to one or more connections, exclude the content item from the communication channel accessible to the one or more connections. 48. The system of claim 47 , wherein the selection is performed by the user. | 0.645659 |
14. A system comprising: a processor; a module configured to control the processor to conduct a dialog exchange between an automated dialog system and a user, the dialog exchange including at least two dialog system prompts and two user input opportunities; and a module configured to determine whether a probability threshold is exceeded that relates to a prediction that continuing the dialog exchange with the user will converge and succeed to a stage consistent with the user's intent or diverge and fail, wherein determining whether the probability threshold is exceeded is based, at least in part, training data on multiple dialog turns in a corpus of dialogs tagged for success or failure after at least two dialog prompts and two user inputs. | 14. A system comprising: a processor; a module configured to control the processor to conduct a dialog exchange between an automated dialog system and a user, the dialog exchange including at least two dialog system prompts and two user input opportunities; and a module configured to determine whether a probability threshold is exceeded that relates to a prediction that continuing the dialog exchange with the user will converge and succeed to a stage consistent with the user's intent or diverge and fail, wherein determining whether the probability threshold is exceeded is based, at least in part, training data on multiple dialog turns in a corpus of dialogs tagged for success or failure after at least two dialog prompts and two user inputs. 15. The system of claim 14 , wherein the dialog training data includes at least one of dialog classification models and extracted dialog features. | 0.628378 |
26. A bowling system for a themed party having one or more animated characters, the bowling system comprising: an automated bowling scoring system in a bowling center, the automated bowling scoring system comprising: a pin detector; a processor for receiving information from the pin detector related to bowling actions; and a display for displaying the one or more animated characters based on signals from the processor; and a party kit comprising: marketing materials for marketing the party kit; party supplies related to the one or more animated characters displayed by the automated bowling scoring system; merchandising items related to the one or more animated characters displayed by the automated bowling scoring system; and gift bags or boxes including gifts for party attendees, each of the gifts having one or more character related to the one or more animated characters displayed by the automated bowling scoring system. | 26. A bowling system for a themed party having one or more animated characters, the bowling system comprising: an automated bowling scoring system in a bowling center, the automated bowling scoring system comprising: a pin detector; a processor for receiving information from the pin detector related to bowling actions; and a display for displaying the one or more animated characters based on signals from the processor; and a party kit comprising: marketing materials for marketing the party kit; party supplies related to the one or more animated characters displayed by the automated bowling scoring system; merchandising items related to the one or more animated characters displayed by the automated bowling scoring system; and gift bags or boxes including gifts for party attendees, each of the gifts having one or more character related to the one or more animated characters displayed by the automated bowling scoring system. 32. The bowling system of claim 26 , wherein the party supplies or gift bags or boxes include a storage medium storing at least one of: a short animation clip that showcases different themes having the one or more animated characters, games, screen savers, screen buddies and a library of characters from the different themes used by the automated bowling scoring system. | 0.5 |
1. An apparatus for rendering an avatar, comprising: a gesture tracker to detect and track a user gesture that corresponds to a canned facial expression, the user gesture including a duration component corresponding to a duration the canned facial expression is to be animated, and in response to a detection and tracking of the user gesture, output one or more animation messages that describe the detection or the tracking of the user gesture or identify the canned facial expression, and the duration; and an animation engine coupled with the gesture tracker to receive the one or more animation messages, and drive an avatar model, in accordance with the one or more animation messages, to animate the avatar with animation of the canned facial expressions for the duration wherein the animation engine is to animate the canned facial expression by blending one or more pre-defined shapes into a neutral face during a start period, hold the avatar at the canned facial expression for the duration during a keep period, and terminate animation of the canned facial expression by un-blending the one or more pre-defined shapes to return the avatar to the neutral face during an end period. | 1. An apparatus for rendering an avatar, comprising: a gesture tracker to detect and track a user gesture that corresponds to a canned facial expression, the user gesture including a duration component corresponding to a duration the canned facial expression is to be animated, and in response to a detection and tracking of the user gesture, output one or more animation messages that describe the detection or the tracking of the user gesture or identify the canned facial expression, and the duration; and an animation engine coupled with the gesture tracker to receive the one or more animation messages, and drive an avatar model, in accordance with the one or more animation messages, to animate the avatar with animation of the canned facial expressions for the duration wherein the animation engine is to animate the canned facial expression by blending one or more pre-defined shapes into a neutral face during a start period, hold the avatar at the canned facial expression for the duration during a keep period, and terminate animation of the canned facial expression by un-blending the one or more pre-defined shapes to return the avatar to the neutral face during an end period. 3. The apparatus of claim 1 , wherein the gesture tracker is to detect and track a user gesture that further includes a facial movement component corresponding to facial movements of the canned facial expression, and in response to a detection of the user gesture, output one or more animation messages that further identify the facial movements; and the animation engine to further drive the avatar model, in accordance with the one or more animation messages, to animate the avatar with animation of the canned facial expressions that includes the facial movements for the duration. | 0.522362 |
12. A network storage server node comprising: a network module using which the node can communicate with a network storage client; a data module using which the node can manage a persistent storage subsystem; and a management host configured to provide management services of the network storage server node and to interface with an external administrative user, the management host including a metadata subsystem to store and retrieve metadata of a plurality of types, relating to a plurality of data objects stored in a distributed object store implemented at least partially in the persistent storage subsystem, wherein the metadata subsystem is configured to store the metadata in locations that are independent of locations where corresponding data objects of the plurality of data objects are stored, the plurality of types of metadata including system defined metadata, inferred metadata and user-defined metadata, wherein the inferred metadata includes latent metadata and discovered metadata, wherein latent metadata includes data gathered by an application from the data associated with the plurality of data objects, the gathered data subsequently being stored as metadata relating to the plurality of data objects, wherein discovered metadata includes relational information derived by the application from the data associated with the plurality of data objects, the relational information describing a relationship between two or more data objects of the plurality of data objects, the metadata subsystem further being capable of searching the metadata of the plurality of types to identify data objects that satisfy user-specified search queries, wherein the metadata subsystem is configured to implement a plurality of mutually isolated query domains, wherein said metadata includes a plurality of metadata attribute-value pairs, wherein each of the metadata attribute-value pairs is assigned to one of the plurality of query domains, wherein each query domain of the plurality of mutually isolated query domains is a logical construct used to isolate the metadata attribute-value pairs assigned to the particular query domain from the metadata attribute-value pairs assigned to the other query domains of the plurality of query domains, and wherein each operation performed by the metadata subsystem is performed within the context of at least one of the plurality of query domains. | 12. A network storage server node comprising: a network module using which the node can communicate with a network storage client; a data module using which the node can manage a persistent storage subsystem; and a management host configured to provide management services of the network storage server node and to interface with an external administrative user, the management host including a metadata subsystem to store and retrieve metadata of a plurality of types, relating to a plurality of data objects stored in a distributed object store implemented at least partially in the persistent storage subsystem, wherein the metadata subsystem is configured to store the metadata in locations that are independent of locations where corresponding data objects of the plurality of data objects are stored, the plurality of types of metadata including system defined metadata, inferred metadata and user-defined metadata, wherein the inferred metadata includes latent metadata and discovered metadata, wherein latent metadata includes data gathered by an application from the data associated with the plurality of data objects, the gathered data subsequently being stored as metadata relating to the plurality of data objects, wherein discovered metadata includes relational information derived by the application from the data associated with the plurality of data objects, the relational information describing a relationship between two or more data objects of the plurality of data objects, the metadata subsystem further being capable of searching the metadata of the plurality of types to identify data objects that satisfy user-specified search queries, wherein the metadata subsystem is configured to implement a plurality of mutually isolated query domains, wherein said metadata includes a plurality of metadata attribute-value pairs, wherein each of the metadata attribute-value pairs is assigned to one of the plurality of query domains, wherein each query domain of the plurality of mutually isolated query domains is a logical construct used to isolate the metadata attribute-value pairs assigned to the particular query domain from the metadata attribute-value pairs assigned to the other query domains of the plurality of query domains, and wherein each operation performed by the metadata subsystem is performed within the context of at least one of the plurality of query domains. 13. A network storage server node as recited in claim 12 , wherein the network storage server node is one of a plurality of network storage server nodes in a clustered network storage system. | 0.54306 |
1. A computer-implemented method in a software development environment for developing product runtime code, the method comprising: identifying a first code component and a second code component, wherein the first code component is in a first runtime language, and wherein the second code component is in a second runtime language, wherein the first runtime language is different than the second runtime language; translating, by a programming interface, the first code component and the second code component into a common development language for development of the code components by: wrapping functions in the first code component in the first runtime language for use in the common development language, and wrapping functions in the second code component in the second runtime language for use in the common development language, wherein the programming interface includes a mapping between functions in the first and second runtime languages and the common development language; determining that the first code component and the second code component have been edited in the common development language; and translating the first edited code component from the common development language into the first runtime language, and the second edited code component into the second runtime language for execution. | 1. A computer-implemented method in a software development environment for developing product runtime code, the method comprising: identifying a first code component and a second code component, wherein the first code component is in a first runtime language, and wherein the second code component is in a second runtime language, wherein the first runtime language is different than the second runtime language; translating, by a programming interface, the first code component and the second code component into a common development language for development of the code components by: wrapping functions in the first code component in the first runtime language for use in the common development language, and wrapping functions in the second code component in the second runtime language for use in the common development language, wherein the programming interface includes a mapping between functions in the first and second runtime languages and the common development language; determining that the first code component and the second code component have been edited in the common development language; and translating the first edited code component from the common development language into the first runtime language, and the second edited code component into the second runtime language for execution. 4. The computer-implemented method of claim 1 , wherein the programming interface is a Java native interface (JNI) and the common development language is Java. | 0.569059 |
1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings. | 1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings. 5. The method of claim 1 wherein the line-wrap function is configured to abbreviate the text string based on a limited space for presentation of the text string on the user interface. | 0.684281 |
7. The method of claim 1 , wherein the first case comprises at least one question presented to the question answering system. | 7. The method of claim 1 , wherein the first case comprises at least one question presented to the question answering system. 8. The method of claim 7 , wherein the first feature comprises at least one of: (i) a type, (ii) a subject matter, (iii) a variable, and (iv) a context of the at least one question. | 0.93623 |
26. The method of claim 25 , wherein the candidate is an individual. | 26. The method of claim 25 , wherein the candidate is an individual. 27. The method of claim 26 , further comprising receiving, at the computer system, the indicated value for the characteristic, wherein the indicated value is received from the candidate. | 0.896111 |
14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. 15. The system of claim 14 , where the server is further to: transmit the refined list of documents to a device of a user that submitted the query. | 0.87307 |
1. A computer-implemented method, comprising: initializing a pseudo-random number generator with an authentication inkblot seed; drawing one or more blots on an authentication inkblot generation canvas to generate an image resembling an inkblot and determining each blot parameter value as a function of one or more pseudo-random values generated by the pseudo-random number generator initialized with the authentication inkblot seed; displaying the authentication inkblot generation canvas on a graphical output device; receiving one or more alphanumeric characters from an input device in response to each displayed authentication inkblot; sending the one or more alphanumeric characters received in response to each displayed authentication inkblot to a security authority as authentication information; and authenticating a user based on a match between the displayed inkblot and the alphanumeric characters. | 1. A computer-implemented method, comprising: initializing a pseudo-random number generator with an authentication inkblot seed; drawing one or more blots on an authentication inkblot generation canvas to generate an image resembling an inkblot and determining each blot parameter value as a function of one or more pseudo-random values generated by the pseudo-random number generator initialized with the authentication inkblot seed; displaying the authentication inkblot generation canvas on a graphical output device; receiving one or more alphanumeric characters from an input device in response to each displayed authentication inkblot; sending the one or more alphanumeric characters received in response to each displayed authentication inkblot to a security authority as authentication information; and authenticating a user based on a match between the displayed inkblot and the alphanumeric characters. 2. The method according to claim 1 , wherein the number of blots drawn on the authentication inkblot generation canvas is a function of one or more pseudo-random values generated by the pseudo-random number generator initialized with the authentication inkblot seed. | 0.685509 |
11. A program product stored on a non-transitional computer-readable storage medium, which when executed, enables a computer system to generate a web service providing a programming interface between a web application and a user application, the program product comprising computer program code for enabling the computer system to: create and store a script of a navigation flow of at least one transaction of the web application, the navigation flow representative of an interaction between a user and a web application interface of the web application during the at least one transaction in the script of the navigation flow; create an store a text file describing a function and at least one of an input parameter or an output parameter, the function to be called by the user application for executing the at least one transaction; create and store web service interface code corresponding to a call of the function as described in the text file; and create and store web service implementation code for executing the interaction based on the script of the navigation flow, wherein the web service implementation code uses the web service interface code to implement the function without the user creating a script including recording the navigation flow of a human user conducting a transaction in the web application. | 11. A program product stored on a non-transitional computer-readable storage medium, which when executed, enables a computer system to generate a web service providing a programming interface between a web application and a user application, the program product comprising computer program code for enabling the computer system to: create and store a script of a navigation flow of at least one transaction of the web application, the navigation flow representative of an interaction between a user and a web application interface of the web application during the at least one transaction in the script of the navigation flow; create an store a text file describing a function and at least one of an input parameter or an output parameter, the function to be called by the user application for executing the at least one transaction; create and store web service interface code corresponding to a call of the function as described in the text file; and create and store web service implementation code for executing the interaction based on the script of the navigation flow, wherein the web service implementation code uses the web service interface code to implement the function without the user creating a script including recording the navigation flow of a human user conducting a transaction in the web application. 14. The program product of claim 11 , wherein the text file is a Web Service Description Language (WSDL) file. | 0.70288 |
2. The method of claim 1 , wherein the user responses are spoken utterances. | 2. The method of claim 1 , wherein the user responses are spoken utterances. 3. The method of claim 2 , wherein, prior to grouping the user responses into groups, transcriptions are obtained for the spoken utterances. | 0.967316 |
1. A method for identifying influential users among a group of users associated with a communication network, the method comprising: selecting two or more ranking models and providing scores to the users in the group using said ranking models based on usage data of the users; calculating a weighing factor for each of the selected ranking models; generating an aggregate score for each user using the weighing factor and the score provided by each one of the selected ranking models; and identifying the influential users based on the aggregate score among the group of users by comparing the aggregate score with a predefined score. | 1. A method for identifying influential users among a group of users associated with a communication network, the method comprising: selecting two or more ranking models and providing scores to the users in the group using said ranking models based on usage data of the users; calculating a weighing factor for each of the selected ranking models; generating an aggregate score for each user using the weighing factor and the score provided by each one of the selected ranking models; and identifying the influential users based on the aggregate score among the group of users by comparing the aggregate score with a predefined score. 4. The method according to claim 1 , further comprising labeling a number of users among the group of users using an active learning process thereby dividing the group of users into labeled users and unlabeled users. | 0.694418 |
1. At a computer system including a multi-touch input display surface, a method for selecting items displayed on the multi-touch input display surface, the method comprising: an act of detecting a first contact with the multi-touch input display surface at a detected first location on the multi-touch input display surface; and an act of detecting a second contact with the multi-touch input display surface at a detected second location on the multi-touch input display surface; an act of calculating a selection region on the multi-touch input display surface based at least on the detected first location and the detected second location, wherein calculating the selection region on the multi-touch input display surface comprises calculating the selection region based on a context at the computer system; an act of selecting one or more items displayed on the multi-touch input display surface in response to the one or more items being at least partially included within at least a portion of the calculated selection region; and an act of rendering item visual feedback at the multi-touch input surface to visually indicate the one or more items having been selected by at least altering display characteristics of the one or more selected items. | 1. At a computer system including a multi-touch input display surface, a method for selecting items displayed on the multi-touch input display surface, the method comprising: an act of detecting a first contact with the multi-touch input display surface at a detected first location on the multi-touch input display surface; and an act of detecting a second contact with the multi-touch input display surface at a detected second location on the multi-touch input display surface; an act of calculating a selection region on the multi-touch input display surface based at least on the detected first location and the detected second location, wherein calculating the selection region on the multi-touch input display surface comprises calculating the selection region based on a context at the computer system; an act of selecting one or more items displayed on the multi-touch input display surface in response to the one or more items being at least partially included within at least a portion of the calculated selection region; and an act of rendering item visual feedback at the multi-touch input surface to visually indicate the one or more items having been selected by at least altering display characteristics of the one or more selected items. 8. The method as recited in claim 1 , wherein the method further includes an act of rending a visible boundary of the selection region. | 0.68 |
1. A system for determining valid citation patterns in text within an electronic document, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions to direct the processor to perform operations comprising: accessing, from the memory, a citation pattern comprising a set of citation components that define a predetermined pattern, each citation component being associated with a set of citation component criteria, comparing text in the electronic document with the citation components of the predetermined pattern, and determining valid citation patterns by identifying text that corresponds to the set of citation components of the predetermined pattern. | 1. A system for determining valid citation patterns in text within an electronic document, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions to direct the processor to perform operations comprising: accessing, from the memory, a citation pattern comprising a set of citation components that define a predetermined pattern, each citation component being associated with a set of citation component criteria, comparing text in the electronic document with the citation components of the predetermined pattern, and determining valid citation patterns by identifying text that corresponds to the set of citation components of the predetermined pattern. 7. The system of claim 1 , wherein comparing includes performing one-to-one pattern matching. | 0.694549 |
1. A method of decoding an encoded video bitstream, said method comprising the steps of: receiving said encoded video bitstream comprising frame header information and macroblock information, said frame header information defining a sequence of frames and each frame being composed of macroblocks represented by said macroblock information; parsing said encoded video bitstream using a first parsing unit and a second parsing unit, each parsing unit independently deriving a full set of parsing state information from said encoded video bitstream on which subsequent parsing of said encoded video bitstream at least partially depends and which identifies data dependencies of frames in said encoded video bitstream, and identifying macroblock information for decoding, and said parsing step includes parsing all of said frame header information in both said first parsing unit and in said second parsing unit such that each parsing unit maintains said full set of said parsing state information for said encoded video bitstream; and allocating each frame of macroblock information to one of said first parsing unit and said second parsing unit, wherein said first parsing unit and said second parsing unit each parse said macroblock information, skipping macroblock information allocated to the other parsing unit, the full set parsing state information derived by each parsing unit identifying data dependencies of at least one frame allocated to the other parsing unit. | 1. A method of decoding an encoded video bitstream, said method comprising the steps of: receiving said encoded video bitstream comprising frame header information and macroblock information, said frame header information defining a sequence of frames and each frame being composed of macroblocks represented by said macroblock information; parsing said encoded video bitstream using a first parsing unit and a second parsing unit, each parsing unit independently deriving a full set of parsing state information from said encoded video bitstream on which subsequent parsing of said encoded video bitstream at least partially depends and which identifies data dependencies of frames in said encoded video bitstream, and identifying macroblock information for decoding, and said parsing step includes parsing all of said frame header information in both said first parsing unit and in said second parsing unit such that each parsing unit maintains said full set of said parsing state information for said encoded video bitstream; and allocating each frame of macroblock information to one of said first parsing unit and said second parsing unit, wherein said first parsing unit and said second parsing unit each parse said macroblock information, skipping macroblock information allocated to the other parsing unit, the full set parsing state information derived by each parsing unit identifying data dependencies of at least one frame allocated to the other parsing unit. 4. The method of decoding an encoded video bitstream as claimed in claim 1 , wherein operation of said first parsing unit and said second parsing unit is controlled with reference to control data. | 0.626234 |
15. A processing system for performing an image search using semantic entities, the processing system comprising: a memory for storing one or more source images and one or more semantic entities associated with at least one of the one or more source images wherein each semantic entity defines a concept with a particular ontology; at least one processor coupled to the memory, the processor configured to: receive a target image as a search query; identify at least one similar image among the one or more source images, the at least one similar image having at least one feature in common with the target image; determine at least one likely semantic entity to describe the target image using the semantic entities associated with the at least one similar image; and use the at least one likely semantic entity to provide search results for the target image. | 15. A processing system for performing an image search using semantic entities, the processing system comprising: a memory for storing one or more source images and one or more semantic entities associated with at least one of the one or more source images wherein each semantic entity defines a concept with a particular ontology; at least one processor coupled to the memory, the processor configured to: receive a target image as a search query; identify at least one similar image among the one or more source images, the at least one similar image having at least one feature in common with the target image; determine at least one likely semantic entity to describe the target image using the semantic entities associated with the at least one similar image; and use the at least one likely semantic entity to provide search results for the target image. 16. The processing system of claim 15 , wherein the at least one processor is further configured to: determine a score for each of the one or more semantic entities; and identify a semantic entity with a highest determined score as the at least one likely semantic entity. | 0.653729 |
31. A method of search, the method, comprising: detecting a set of location identifiers of webpages that match a specified pattern that is not a unified resource identifier (URI), the specified pattern being stored in a computer-readable storage medium; wherein, the specified pattern corresponds to a semantic type; identifying a set of search results as having content related to the semantic type; identifying a set of type-determined webpages having the matching location identifiers; data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining; generating a refined set of search results from the refined set of type-determined web pages; and ranking each of the set of type-determined web pages based on the relevancy determined from the data mining; wherein, the semantic type is associated with multiple attributes that are user-defined; and wherein, the set of search results includes objects associated with the set of location identifiers having the specified pattern. | 31. A method of search, the method, comprising: detecting a set of location identifiers of webpages that match a specified pattern that is not a unified resource identifier (URI), the specified pattern being stored in a computer-readable storage medium; wherein, the specified pattern corresponds to a semantic type; identifying a set of search results as having content related to the semantic type; identifying a set of type-determined webpages having the matching location identifiers; data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining; generating a refined set of search results from the refined set of type-determined web pages; and ranking each of the set of type-determined web pages based on the relevancy determined from the data mining; wherein, the semantic type is associated with multiple attributes that are user-defined; and wherein, the set of search results includes objects associated with the set of location identifiers having the specified pattern. 33. The method of claim 31 , wherein, the location identifier is a Universal Resource Identifier (URI) or Universal Resource Locator (URL); and wherein, the objects are web pages. | 0.73037 |
1. A method to detect, diagnose, and mitigate issues in a network, the method comprising: receiving Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network; receiving external data related to the network, the external data describing events related to any one or more of construction, weather, natural disasters, and planned outages; instantiating a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly; performing one or more actions based on the evaluating the one or more rules; and analyzing the external data to determine a relationship between the events and network elements in the network, wherein the relationship comprises any one or more of distance, amount of time the event exists, a number of events in a shared area, reputation of an event based on historical data, and a magnitude of collateral damage an event may cause to generate an associated risk level. | 1. A method to detect, diagnose, and mitigate issues in a network, the method comprising: receiving Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network; receiving external data related to the network, the external data describing events related to any one or more of construction, weather, natural disasters, and planned outages; instantiating a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly; performing one or more actions based on the evaluating the one or more rules; and analyzing the external data to determine a relationship between the events and network elements in the network, wherein the relationship comprises any one or more of distance, amount of time the event exists, a number of events in a shared area, reputation of an event based on historical data, and a magnitude of collateral damage an event may cause to generate an associated risk level. 6. The method of claim 1 , wherein the one or more actions comprise suggesting a new link in the network or suggesting traffic rearranging to free up capacity on some links. | 0.909751 |
1. A system comprising: a plurality of student wireless communication devices, each having: a display; a user-operable input device; a network transceiver configured to communicate with a wireless communication network using frequencies licensed for wide-area networks; a short-range non-network transceiver; a controller configured to control operation of the non-network transceiver of the first wireless communication device; and an instructor wireless communication device having at least the short-range non-network transceiver and the controller configured to control operation of the non-network transceiver of the instructor wireless communication device; a wireless access point (AP) configured to transmit the beacon signal wherein the short-range non-network transceiver in each of the plurality of student wireless communication devices is configured to communicate with the instructor wireless communication device via the AP whereby the short-range communication link between the respective short-range non-network transceivers and the instructor wireless communication device is established via the AP; wherein the controller in each of the student wireless communication devices is configured to automatically detect the transmitted beacon signal and to establish a short-range communication link between the respective short-range non-network transceivers and the instructor wireless communication device via the AP and to exchange data, including student response data, with the instructor wireless communication device, and upon establishing the short-range communication link, automatically performing an authentication process for each student wireless communication device, and temporarily disabling the respective network transceivers upon authentication during a period of time in which the short-range communication link is established; and wherein the controller in the instructor wireless communication device is configured to receive data from any responding ones of the plurality of student wireless communication devices via the AP. | 1. A system comprising: a plurality of student wireless communication devices, each having: a display; a user-operable input device; a network transceiver configured to communicate with a wireless communication network using frequencies licensed for wide-area networks; a short-range non-network transceiver; a controller configured to control operation of the non-network transceiver of the first wireless communication device; and an instructor wireless communication device having at least the short-range non-network transceiver and the controller configured to control operation of the non-network transceiver of the instructor wireless communication device; a wireless access point (AP) configured to transmit the beacon signal wherein the short-range non-network transceiver in each of the plurality of student wireless communication devices is configured to communicate with the instructor wireless communication device via the AP whereby the short-range communication link between the respective short-range non-network transceivers and the instructor wireless communication device is established via the AP; wherein the controller in each of the student wireless communication devices is configured to automatically detect the transmitted beacon signal and to establish a short-range communication link between the respective short-range non-network transceivers and the instructor wireless communication device via the AP and to exchange data, including student response data, with the instructor wireless communication device, and upon establishing the short-range communication link, automatically performing an authentication process for each student wireless communication device, and temporarily disabling the respective network transceivers upon authentication during a period of time in which the short-range communication link is established; and wherein the controller in the instructor wireless communication device is configured to receive data from any responding ones of the plurality of student wireless communication devices via the AP. 8. The system of claim 1 wherein each of the plurality of student wireless communication devices is configured to perform a disconnection process with the instructor wireless communication device upon termination of the short-range communication link between the respective short-range non-network transceivers and the instructor wireless communication device and to enable the respective network transceivers upon disconnection. | 0.594353 |
1. A computer-implemented method for producing web pages, the method comprising: converting audio signals within a plurality of multimedia content elements into a text-searchable representation of the multimedia content elements, the multimedia content elements comprising video or audio; creating, for each topic in subset of topics, a query string comprising tags associated with a set of the multimedia content elements, the query string associated with the topic; creating a content catalog from the text-searchable representation of the multimedia content elements, wherein the creating the content catalog includes: extracting keywords from the text-searchable representation and associating the keywords with respective multimedia content elements from which the keywords were extracted, augmenting the extracted keywords with additional text and phrases related to one or more of the tags and the keywords and associating the additional text and phrases with the respective multimedia content elements, and calculating relevancy scores for each multimedia content element of the plurality of the multimedia content elements based on confidence levels comprising a confidence that text-searchable index accurately represents the audio signals, a confidence that the tags accurately represent the text searchable index, and a confidence that the multimedia content elements match the tags in the query string; executing a query against the content catalog using a topic listing to identify a subset of topics referenced in the multimedia content elements and, for a topic within the subset of topics, a set of the multimedia content elements related thereto; and executing, in response to a request to display information about the topic within the subset of topics; and producing dynamically-created web page in response the request to display information about the topic within the subset of topics, wherein the dynamically-created web page comprises links to the multimedia content elements having a minimum relevancy score, wherein the links to the multimedia content elements are ordered based on one or more of relevancy scores of the respective multimedia content elements and a date associated with each multimedia content element of the multimedia content elements. | 1. A computer-implemented method for producing web pages, the method comprising: converting audio signals within a plurality of multimedia content elements into a text-searchable representation of the multimedia content elements, the multimedia content elements comprising video or audio; creating, for each topic in subset of topics, a query string comprising tags associated with a set of the multimedia content elements, the query string associated with the topic; creating a content catalog from the text-searchable representation of the multimedia content elements, wherein the creating the content catalog includes: extracting keywords from the text-searchable representation and associating the keywords with respective multimedia content elements from which the keywords were extracted, augmenting the extracted keywords with additional text and phrases related to one or more of the tags and the keywords and associating the additional text and phrases with the respective multimedia content elements, and calculating relevancy scores for each multimedia content element of the plurality of the multimedia content elements based on confidence levels comprising a confidence that text-searchable index accurately represents the audio signals, a confidence that the tags accurately represent the text searchable index, and a confidence that the multimedia content elements match the tags in the query string; executing a query against the content catalog using a topic listing to identify a subset of topics referenced in the multimedia content elements and, for a topic within the subset of topics, a set of the multimedia content elements related thereto; and executing, in response to a request to display information about the topic within the subset of topics; and producing dynamically-created web page in response the request to display information about the topic within the subset of topics, wherein the dynamically-created web page comprises links to the multimedia content elements having a minimum relevancy score, wherein the links to the multimedia content elements are ordered based on one or more of relevancy scores of the respective multimedia content elements and a date associated with each multimedia content element of the multimedia content elements. 7. The method of claim 1 further comprising compiling the additional text and phrases from topic lists. | 0.570796 |
34. A text input method executable by an electronic device connectable to a display and capable of detecting touch operations, comprising: displaying a virtual keyboard comprising a plurality of keys; utilizing the virtual keyboard as a base for one or more touch operations detectable by a touch detection function, wherein each key of the plurality of keys is operable as a toggle key and is associated with one or more characters for input to a text area; discriminating a detected touch movement track based from a first activated key of the plurality of keys of the virtual keyboard as an intra-keystroke moving operation or an inter-keystroke moving operation even if the detected touch movement track is performed over the virtual keyboard; selecting of an option in a first graphical user interface component in response to the detected touch movement track upon a condition that the detected touch movement track comprises an intra-keystroke moving operation even if the first graphical user interface component is separated from the detected touch movement track; selecting a basic character set of one or more characters upon a condition that the detected touch movement track comprises the inter-keystroke moving operation which comprises a touch operation representing transition from activation of the first activated key of the plurality of keys of the virtual keyboard to activation of a second activated key of the plurality of keys of the virtual keyboard, wherein the basic character set comprises one or more characters associated with the first activated key and the second activated key; retrieving an expanded character set of one or more characters based on the basic character set, wherein the expanded character set comprises characters related to the first activated key and the second activated key, and the number of characters in the expanded character set is more than the number of characters in the basic character set; generating an auto-completed word based on a database of words in response to the touch operation representing transition, wherein the auto-completed word comprises a plurality of characters, and each of the plurality of characters of the auto-completed word is selected from the expanded character set; presenting the auto-completed word as an option in a second graphical user interface component in response to the touch operation representing transition; and entering the auto-completed word to the text area in response to an assistant touch operation associated with the option in the second graphical user interface component, wherein the assistant touch operation is detectable by the touch detection function. | 34. A text input method executable by an electronic device connectable to a display and capable of detecting touch operations, comprising: displaying a virtual keyboard comprising a plurality of keys; utilizing the virtual keyboard as a base for one or more touch operations detectable by a touch detection function, wherein each key of the plurality of keys is operable as a toggle key and is associated with one or more characters for input to a text area; discriminating a detected touch movement track based from a first activated key of the plurality of keys of the virtual keyboard as an intra-keystroke moving operation or an inter-keystroke moving operation even if the detected touch movement track is performed over the virtual keyboard; selecting of an option in a first graphical user interface component in response to the detected touch movement track upon a condition that the detected touch movement track comprises an intra-keystroke moving operation even if the first graphical user interface component is separated from the detected touch movement track; selecting a basic character set of one or more characters upon a condition that the detected touch movement track comprises the inter-keystroke moving operation which comprises a touch operation representing transition from activation of the first activated key of the plurality of keys of the virtual keyboard to activation of a second activated key of the plurality of keys of the virtual keyboard, wherein the basic character set comprises one or more characters associated with the first activated key and the second activated key; retrieving an expanded character set of one or more characters based on the basic character set, wherein the expanded character set comprises characters related to the first activated key and the second activated key, and the number of characters in the expanded character set is more than the number of characters in the basic character set; generating an auto-completed word based on a database of words in response to the touch operation representing transition, wherein the auto-completed word comprises a plurality of characters, and each of the plurality of characters of the auto-completed word is selected from the expanded character set; presenting the auto-completed word as an option in a second graphical user interface component in response to the touch operation representing transition; and entering the auto-completed word to the text area in response to an assistant touch operation associated with the option in the second graphical user interface component, wherein the assistant touch operation is detectable by the touch detection function. 36. The text input method as claimed in claim 34 , wherein concatenation of each of the plurality of characters of the auto-completed word comprises a meaningful word determined based on a dictionary or a database of words that comprises most-frequently input words. | 0.7791 |
1. A method comprising: determining an estimated number of items that match a first structured query by a computing device, wherein the first structured query comprises one or more attributes values and each attribute value is associated with an attribute; determining if the estimated number of items is below a threshold number of items by the computing device; and if the estimated number of items is below the threshold number of items: determining a plurality of candidate structured queries from the first structured query by the computing device, wherein the number of candidate structured queries in the plurality of candidate structured queries is proportional to a maximum time, wherein the number of candidate structured queries is determined by dividing the maximum time by the expected amount of time it takes to determine and evaluate a candidate structured query; for each candidate structured query of the candidate structured queries, estimating a distance between an item that matches the candidate structured query and the first structured query based on the attribute values associated with the first structured query, one or more attribute values associated with the item that matched the candidate structured query, and popularity information associated with the item that matched the candidate structured query by the computing device; determining the candidate structured query with a smallest determined distance as a second structured query by the computing device; determining a plurality of items that match the second structured query by the computing device; and providing indicators of each of the determined plurality of items by the computing device through a network. | 1. A method comprising: determining an estimated number of items that match a first structured query by a computing device, wherein the first structured query comprises one or more attributes values and each attribute value is associated with an attribute; determining if the estimated number of items is below a threshold number of items by the computing device; and if the estimated number of items is below the threshold number of items: determining a plurality of candidate structured queries from the first structured query by the computing device, wherein the number of candidate structured queries in the plurality of candidate structured queries is proportional to a maximum time, wherein the number of candidate structured queries is determined by dividing the maximum time by the expected amount of time it takes to determine and evaluate a candidate structured query; for each candidate structured query of the candidate structured queries, estimating a distance between an item that matches the candidate structured query and the first structured query based on the attribute values associated with the first structured query, one or more attribute values associated with the item that matched the candidate structured query, and popularity information associated with the item that matched the candidate structured query by the computing device; determining the candidate structured query with a smallest determined distance as a second structured query by the computing device; determining a plurality of items that match the second structured query by the computing device; and providing indicators of each of the determined plurality of items by the computing device through a network. 3. The method of claim 1 , further comprising: for each candidate structured query of the plurality of candidate structured queries, estimating a number of items that match the candidate structured query; and determining the candidate structured query with the highest estimated number of items as the second structured query. | 0.811419 |
18. The method of claim 14 further comprising, constructing the interface including an input field and an output field to be an object, which is selectable from the search-engine response page to be copied and stored in another medium. | 18. The method of claim 14 further comprising, constructing the interface including an input field and an output field to be an object, which is selectable from the search-engine response page to be copied and stored in another medium. 19. The method of claim 18 , wherein the interface including the input field and the output field are collectively selectable from the search-engine response page by way of a drag-and-drop input. | 0.932877 |
1. A method implemented at least in part by a computing device, the method comprising: displaying a primary URL; displaying a final destination URL associated with the primary URL; creating an instance of a browser application in a secure environment; extracting client identification information from a Client ID (cid) field in the final destination URL; blocking the final destination URL if the final destination URL contains a particular client ID; and directly visiting the final destination URL using the browser application if the final destination URL does not contain the particular client ID. | 1. A method implemented at least in part by a computing device, the method comprising: displaying a primary URL; displaying a final destination URL associated with the primary URL; creating an instance of a browser application in a secure environment; extracting client identification information from a Client ID (cid) field in the final destination URL; blocking the final destination URL if the final destination URL contains a particular client ID; and directly visiting the final destination URL using the browser application if the final destination URL does not contain the particular client ID. 2. The method of claim 1 wherein the displaying a final destination URL comprises accessing a browsing history file wherein the browsing history file comprises the primary URL and the final destination URL. | 0.662439 |
1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary. | 1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary. 3. The method of claim 1 , wherein identifying the neighborhood further includes determining that the identified cluster contains at least a threshold amount of geographic locations. | 0.53682 |
12. The cascading learning system of claim 1 , wherein the cluster manager further comprises a module generator configured to organize data structures and data clusters in the request dispatcher and classifier and the search module container. | 12. The cascading learning system of claim 1 , wherein the cluster manager further comprises a module generator configured to organize data structures and data clusters in the request dispatcher and classifier and the search module container. 13. The cascading learning system of claim 12 , wherein the cluster manager further comprises a training and test set container module configured to manage training, validation, and test sets for artificial neural networks (ANN) and feed-forward neural networks (FFNN), and to control cluster data flow of input data used in each domain-specific module. | 0.872352 |
1. A computing system comprising: hardware; a database engine implemented by the hardware; and, middleware integrated within the database engine and implemented by the hardware to execute a functional-form query representing a dataflow graph comprising a plurality of queries and a plurality of relation valued functions, wherein the middleware is to interact with the database engine to cause the database engine to execute the queries, and wherein each relation valued function receives a plurality of first relations as input and generates a second relation as output. | 1. A computing system comprising: hardware; a database engine implemented by the hardware; and, middleware integrated within the database engine and implemented by the hardware to execute a functional-form query representing a dataflow graph comprising a plurality of queries and a plurality of relation valued functions, wherein the middleware is to interact with the database engine to cause the database engine to execute the queries, and wherein each relation valued function receives a plurality of first relations as input and generates a second relation as output. 11. The computing system of claim 1 , wherein the middleware comprises a first component to extend functionality of the database engine to support the relation valued functions to integrate applications into the queries that are evaluated by the database engine. | 0.772396 |
18. A system for dynamically ranking, links to items of audio content returned to a user in response to the execution of a query by a search engine, tile system comprising: a search provider comprising a data store, wherein the data store comprise a storage device for persistent storage of information, and a query planner component, the query planner component parsing a query into one or more logical units and annotating the one or more logical units with category information, wherein annotating includes an annotation related to audio content; identifying a context of search according to the query, to identify links and the annotation for each of the one or more logical units; a search engine receiving a query and searching an index to identify links to items of audio content responsive to the query, tile search engine further selecting the ranking heuristic comprising an algorithm for ranking items of audio content available from structured sources higher than audio content available from unstructured sources, the search engine even further generating a result set that is ranked according to the context of search and annotations for each of the one or more logical units as annotated by the query planner; and providing, through the search provider, a set of links for navigating to a preferred provider of an item in the result set, wherein the preferred provider provides audio content and is designated by a user in a user profile. | 18. A system for dynamically ranking, links to items of audio content returned to a user in response to the execution of a query by a search engine, tile system comprising: a search provider comprising a data store, wherein the data store comprise a storage device for persistent storage of information, and a query planner component, the query planner component parsing a query into one or more logical units and annotating the one or more logical units with category information, wherein annotating includes an annotation related to audio content; identifying a context of search according to the query, to identify links and the annotation for each of the one or more logical units; a search engine receiving a query and searching an index to identify links to items of audio content responsive to the query, tile search engine further selecting the ranking heuristic comprising an algorithm for ranking items of audio content available from structured sources higher than audio content available from unstructured sources, the search engine even further generating a result set that is ranked according to the context of search and annotations for each of the one or more logical units as annotated by the query planner; and providing, through the search provider, a set of links for navigating to a preferred provider of an item in the result set, wherein the preferred provider provides audio content and is designated by a user in a user profile. 20. The system of claim 18 wherein the search engine is operative to receive the query from the query planner component. | 0.542258 |
15. A computerized method of presenting web pages comprising: a) at a first server computer, operating software to: i) crawl original web pages stored on remote web servers to identify a quoting web page containing a quotation of a quoted text portion, ii) identify a quoted web page for the quoted text portion based on a context in which the quotation was found in the quoting web page, the quoted web page being stored on one of the remote web servers, and iii) store in a database: ( 1 ) a first identifier that identifies the quoting web page, ( 2 ) a second identifier that identifies the quoted web page, ( 3 ) a third identifier that identifies the quoted text portion, and iv) repeats i), ii), and iii) to identify and store information about a plurality of quoting web pages, a plurality of quoted text portions, and a plurality of quoting web pages; and b) at a second server computer, operating software to: i) receive from a browser operating on a user computer a particular second identifier for a particular quoted web page; ii) query the database to identify multiple quoted text portions and multiple quoting web pages for the particular quoted web page; iii) generating a revised web page based on: ( 1 ) the particular quoted web page stored on one of the remote web servers, ( 2 ) the multiple quoted text portions identified by the database query, and ( 3 ) and the multiple quoting web pages identified by the database query, wherein the revised web page highlights the multiple quoted text portions in the particular quoted web page and links to the multiple quoting web pages that quoted the multiple quoted text portions; iv) transmitting the revised web page to the browser software for display on the user computer. | 15. A computerized method of presenting web pages comprising: a) at a first server computer, operating software to: i) crawl original web pages stored on remote web servers to identify a quoting web page containing a quotation of a quoted text portion, ii) identify a quoted web page for the quoted text portion based on a context in which the quotation was found in the quoting web page, the quoted web page being stored on one of the remote web servers, and iii) store in a database: ( 1 ) a first identifier that identifies the quoting web page, ( 2 ) a second identifier that identifies the quoted web page, ( 3 ) a third identifier that identifies the quoted text portion, and iv) repeats i), ii), and iii) to identify and store information about a plurality of quoting web pages, a plurality of quoted text portions, and a plurality of quoting web pages; and b) at a second server computer, operating software to: i) receive from a browser operating on a user computer a particular second identifier for a particular quoted web page; ii) query the database to identify multiple quoted text portions and multiple quoting web pages for the particular quoted web page; iii) generating a revised web page based on: ( 1 ) the particular quoted web page stored on one of the remote web servers, ( 2 ) the multiple quoted text portions identified by the database query, and ( 3 ) and the multiple quoting web pages identified by the database query, wherein the revised web page highlights the multiple quoted text portions in the particular quoted web page and links to the multiple quoting web pages that quoted the multiple quoted text portions; iv) transmitting the revised web page to the browser software for display on the user computer. 17. The computerized method of claim 15 , wherein the third identifier of the quoted text portion that is stored in the database is text that comprises the quoted text portion. | 0.567745 |
12. A computer-readable storage medium containing instructions for controlling a computer system to identify significant sentences of a document, by a method comprising: providing a classifier that is trained by providing a training set of training documents along with an indication of whether words of the document are important or not important as indicated by a person; for each training document, generating multiple scores for each word indicated as being important or not important using different scoring techniques to generate a technique-specific importance of the word to the training document, the multiple scores for each word forming a feature vector; and training a classifier to classify words as important or not important to a document based on the feature vectors representing the multiple scores for the words generated from different scoring techniques and based on the indications of whether the words are important or not important; generating scores using the different scoring techniques for words of the document, the multiple scores for a word of the document being a feature vector; identifying important words of the document using the classifier to classify from the feature vectors those words that are important to the document; calculating significance of sentences of the document based on the identified important words contained in the sentences; and storing an indication of the calculated significance of the documents. | 12. A computer-readable storage medium containing instructions for controlling a computer system to identify significant sentences of a document, by a method comprising: providing a classifier that is trained by providing a training set of training documents along with an indication of whether words of the document are important or not important as indicated by a person; for each training document, generating multiple scores for each word indicated as being important or not important using different scoring techniques to generate a technique-specific importance of the word to the training document, the multiple scores for each word forming a feature vector; and training a classifier to classify words as important or not important to a document based on the feature vectors representing the multiple scores for the words generated from different scoring techniques and based on the indications of whether the words are important or not important; generating scores using the different scoring techniques for words of the document, the multiple scores for a word of the document being a feature vector; identifying important words of the document using the classifier to classify from the feature vectors those words that are important to the document; calculating significance of sentences of the document based on the identified important words contained in the sentences; and storing an indication of the calculated significance of the documents. 22. The computer-readable storage medium of claim 12 wherein the document is an electronic mail message. | 0.563676 |
17. A system comprising: one or more computers comprising one or more processors; and one or more storage devices storing instructions that are configured to, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a search specification, the search specification comprising a query modification description and a result modification description; generating, based on at least one of the query modification description or the result modification description, query modification data, one or more label definitions, and result modification data; receiving a search query; modifying the search query based on the query modification data; submitting the modified search query to a search engine and receiving ordered results from the search engine in response; applying a label to at least a portion of the ordered results based on the one or more label definitions; modifying the ordered results based on the applied label and the result modification data; and outputting the modified results as a response to the search query. | 17. A system comprising: one or more computers comprising one or more processors; and one or more storage devices storing instructions that are configured to, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a search specification, the search specification comprising a query modification description and a result modification description; generating, based on at least one of the query modification description or the result modification description, query modification data, one or more label definitions, and result modification data; receiving a search query; modifying the search query based on the query modification data; submitting the modified search query to a search engine and receiving ordered results from the search engine in response; applying a label to at least a portion of the ordered results based on the one or more label definitions; modifying the ordered results based on the applied label and the result modification data; and outputting the modified results as a response to the search query. 19. The system of claim 17 , wherein: the label definitions include a uniform resource locator (URL) label for applying to at least one URL in the results; and applying the label to at least a portion of the ordered results includes applying the URL label to a result in the results, the result being associated with the URL. | 0.616803 |
16. A system comprising: a print controller operable to receive print data for a print job, to receive a communication defined according to a first language, to receive a job ticket defined according to a second language and wrapped in the communication, to analyze the communication to identify the job ticket, to extract the job ticket from the communication defined according to the first language, and to process the received print data in accordance with the job ticket defined according to the second language. | 16. A system comprising: a print controller operable to receive print data for a print job, to receive a communication defined according to a first language, to receive a job ticket defined according to a second language and wrapped in the communication, to analyze the communication to identify the job ticket, to extract the job ticket from the communication defined according to the first language, and to process the received print data in accordance with the job ticket defined according to the second language. 20. The system of claim 16 wherein: the print controller is further operable to identify multiple communications that each wrap a job ticket for the print job that is defined according to the second language, and to extract the job tickets from the communications for processing with the print data. | 0.599127 |
1. A method for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the method comprising: using a computer system to execute method steps comprising: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user based on the feedback received, where for each of the search results that receive feedback, a plurality of feedback values are determined and are used to construct a model that includes profile weights computed from the feedback values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made by combining the internal weights with the profile weights in the constructed model, wherein the internal weights are modified according to a function of the internal weights used for scoring search criteria and of the profile weights; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. | 1. A method for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the method comprising: using a computer system to execute method steps comprising: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user based on the feedback received, where for each of the search results that receive feedback, a plurality of feedback values are determined and are used to construct a model that includes profile weights computed from the feedback values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made by combining the internal weights with the profile weights in the constructed model, wherein the internal weights are modified according to a function of the internal weights used for scoring search criteria and of the profile weights; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. 14. The method of claim 1 , wherein the function is selected from a group consisting of: log frequency, log inverse frequency, linear frequency, fuzzy frequency, fuzzy inverse frequency, and any combination of these. | 0.593182 |
6. The method of claim 1 , further comprising: identifying at least one of the current device and application to which the description corresponds using a noun phrase of the description; selecting a noun phrase-resolution script (NPRS) that corresponds to at least one of the identified current device and application and accessing noun phrase-resolution rules via the selected NPRS; and translating the description to generate the query that corresponds to at least one of the device and the description using the noun phrase-resolution rules. | 6. The method of claim 1 , further comprising: identifying at least one of the current device and application to which the description corresponds using a noun phrase of the description; selecting a noun phrase-resolution script (NPRS) that corresponds to at least one of the identified current device and application and accessing noun phrase-resolution rules via the selected NPRS; and translating the description to generate the query that corresponds to at least one of the device and the description using the noun phrase-resolution rules. 11. The method of claim 6 , wherein generating the query includes translating a noun phrase of the description into the object. | 0.900791 |
24. A computer program, residing on a computer readable medium, for a speech recognition system comprising a processor and an input device, the computer program comprising instructions performing speech recognition by causing the processor to perform the following operations: receive language model results for speech recognition candidates for an utterance from multiple language models; combine the results from the multiple language models according to a combination expression to produce combined language model results, the combination expression applying different combination weights to the results received from the respective language models; evaluate the candidates using the combined language model results to select one of the candidates; adjust at least one of the combination expression weights based on the selected candidate; and repeat the combining, selecting, and adjusting for a subsequent utterance. | 24. A computer program, residing on a computer readable medium, for a speech recognition system comprising a processor and an input device, the computer program comprising instructions performing speech recognition by causing the processor to perform the following operations: receive language model results for speech recognition candidates for an utterance from multiple language models; combine the results from the multiple language models according to a combination expression to produce combined language model results, the combination expression applying different combination weights to the results received from the respective language models; evaluate the candidates using the combined language model results to select one of the candidates; adjust at least one of the combination expression weights based on the selected candidate; and repeat the combining, selecting, and adjusting for a subsequent utterance. 25. The computer program of claim 24, further comprising instructions for causing a processor to: prompt a user to identify a source of text; retrieve text from the source of text identified by the user; and build a topic language model from the retrieved text. | 0.5 |
19. The method of claim 18 , wherein the performing speech recognition based at least in part on a language model associated with the speaker includes: generating the language model based on communications generated by the speaker. | 19. The method of claim 18 , wherein the performing speech recognition based at least in part on a language model associated with the speaker includes: generating the language model based on communications generated by the speaker. 20. The method of claim 19 , wherein the generating the language model based on communications generated by the speaker includes: generating the language model based on emails transmitted by the speaker, documents authored by the speaker, and/or social network messages transmitted by the speaker. | 0.857461 |
17. A method, comprising: receiving a plurality of parameters based, at least in part, on metadata information obtained from data mining one or more databases, at least one database containing tags associated with objects, wherein the data mining is to apply one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by a capture system, wherein the security policy controls network communications captured by the capture system. | 17. A method, comprising: receiving a plurality of parameters based, at least in part, on metadata information obtained from data mining one or more databases, at least one database containing tags associated with objects, wherein the data mining is to apply one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by a capture system, wherein the security policy controls network communications captured by the capture system. 18. The method of claim 17 , further comprising: generating a capture rule for capturing items intended to be propagated as part of the network communications; and generating a discovery rule for objects to be registered for future rule creations. | 0.613089 |
26. The computer readable storage medium of claim 21 , further comprising the steps of: performing an endpointing search on said augmented audio signal; and applying speech recognition processing to the endpointed audio signal. | 26. The computer readable storage medium of claim 21 , further comprising the steps of: performing an endpointing search on said augmented audio signal; and applying speech recognition processing to the endpointed audio signal. 27. The computer readable storage medium of claim 26 , wherein said endpointing search comprises the steps of: locating at least a first speech endpoint in said audio signal using a first Hidden Markov Model; and locating a second speech endpoint in said audio signal, such that at least a portion of said audio signal located between said first speech endpoint and said second speech endpoint represents speech. | 0.783186 |
1. A computing system for controlling access to a plurality of objects, the computing system comprising: a processor; and memory that stores a scoped access control metadata element that controls access to a plurality of objects that are stored in a computer storage medium of the computing system, wherein the scoped access control metadata element comprises: a resource scope statement that identifies a plurality of objects for which the scoped access control metadata element provides access rights by defining a portion of a directory hierarchy indicating that the scoped access control metadata element provides access rights for a plurality of file objects located at or below the specified portion of the directory hierarchy; and a rules statement that includes a plurality of rule statements that each define different access control rules for accessing the plurality of objects, including: a first rule statement that includes: a first statement scope that identifies a first set of one or more users to whom the first rule statement applies and who may access the plurality of objects, including a rule that defines the first set of one or more users as users that have been authenticated; and a first grant statement that defines what access rights the first set of one or more users are granted for accessing any one of the plurality of objects; and a second rule statement that includes: a second statement scope that identifies a second set of one or more users to whom the second rule statement applies and who may also access the plurality of objects; and a second grant statement that defines what different access rights the second set of one or more users are granted for accessing any one of the plurality of objects, the computing system further comprising memory that stores computer-executable instructions that, when executed, implement a method, comprising: receiving a request from a user to access one of the plurality of file objects, the user included in one or more of the first set of one or more users or the second set of one or more users; determining that the scoped access control metadata element provides access rights to the one of the plurality of file objects; and granting the user access to the one of the plurality of file objects, as defined by the scoped access control metadata element. | 1. A computing system for controlling access to a plurality of objects, the computing system comprising: a processor; and memory that stores a scoped access control metadata element that controls access to a plurality of objects that are stored in a computer storage medium of the computing system, wherein the scoped access control metadata element comprises: a resource scope statement that identifies a plurality of objects for which the scoped access control metadata element provides access rights by defining a portion of a directory hierarchy indicating that the scoped access control metadata element provides access rights for a plurality of file objects located at or below the specified portion of the directory hierarchy; and a rules statement that includes a plurality of rule statements that each define different access control rules for accessing the plurality of objects, including: a first rule statement that includes: a first statement scope that identifies a first set of one or more users to whom the first rule statement applies and who may access the plurality of objects, including a rule that defines the first set of one or more users as users that have been authenticated; and a first grant statement that defines what access rights the first set of one or more users are granted for accessing any one of the plurality of objects; and a second rule statement that includes: a second statement scope that identifies a second set of one or more users to whom the second rule statement applies and who may also access the plurality of objects; and a second grant statement that defines what different access rights the second set of one or more users are granted for accessing any one of the plurality of objects, the computing system further comprising memory that stores computer-executable instructions that, when executed, implement a method, comprising: receiving a request from a user to access one of the plurality of file objects, the user included in one or more of the first set of one or more users or the second set of one or more users; determining that the scoped access control metadata element provides access rights to the one of the plurality of file objects; and granting the user access to the one of the plurality of file objects, as defined by the scoped access control metadata element. 12. The computing system of claim 1 , wherein the first rule statement also includes a deny statement that defines what access rights the first set of one or more users are denied for accessing any one of the plurality of objects. | 0.571927 |
10. A computer implemented method comprising: under control of one or more processors configured with executable instructions: identifying a language usable for a password; identifying permissible characters that may be used in the password; identifying a maximum character position permissible for the password; determining, for each character position up to the maximum character position, a frequency at which each of the permissible characters is used at the respective character position in words of the identified language; for each position, arranging the permissible characters into character strings based on the determined frequency at which each character is used at the respective position in words of the identified language, such that each character string begins with a permissible character most frequently used at the respective position and ends with a permissible character least frequently used at the respective position; storing the character strings in memory; generating words, one after another, the words having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from the respective character strings stored in memory for that position and in an order based at least in part on a character string, beginning with the character that is most frequently used at the respective position in the words of the identified language; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. | 10. A computer implemented method comprising: under control of one or more processors configured with executable instructions: identifying a language usable for a password; identifying permissible characters that may be used in the password; identifying a maximum character position permissible for the password; determining, for each character position up to the maximum character position, a frequency at which each of the permissible characters is used at the respective character position in words of the identified language; for each position, arranging the permissible characters into character strings based on the determined frequency at which each character is used at the respective position in words of the identified language, such that each character string begins with a permissible character most frequently used at the respective position and ends with a permissible character least frequently used at the respective position; storing the character strings in memory; generating words, one after another, the words having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from the respective character strings stored in memory for that position and in an order based at least in part on a character string, beginning with the character that is most frequently used at the respective position in the words of the identified language; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. 13. The method of claim 10 , wherein the frequency that each of the characters occurs at each position is determined based on a study of a sample of existing passwords. | 0.5 |
13. The medium of claim 12 , wherein the service includes advice. | 13. The medium of claim 12 , wherein the service includes advice. 14. The medium of claim 13 , wherein the method further comprises authenticating the user in the telephone call via a personal identification number to charge the user for the advice. | 0.931162 |
1. A method comprising: scanning data that is maintained on multiple social networks, wherein scanning comprises identifying, by one or more processors, data that is associated with a social entity; determining one or more characteristics of the identified data; generating, for each of the one or more characteristics, a reference to the identified data that indicates the characteristic; algorithmically comparing one or more generated references to one or more known references, wherein the one or more known references are references to characteristics of identified data that have been assigned a level of risk, and wherein the one or more generated references that are compared to the one or more known references are dynamically selected from a group of generated references; determining, based on the algorithmic comparisons, a risk score for a social entity; and determining, based on a statistical algorithm, a confidence score for the risk score, wherein the confidence score indicates the reliability of the determined risk score. | 1. A method comprising: scanning data that is maintained on multiple social networks, wherein scanning comprises identifying, by one or more processors, data that is associated with a social entity; determining one or more characteristics of the identified data; generating, for each of the one or more characteristics, a reference to the identified data that indicates the characteristic; algorithmically comparing one or more generated references to one or more known references, wherein the one or more known references are references to characteristics of identified data that have been assigned a level of risk, and wherein the one or more generated references that are compared to the one or more known references are dynamically selected from a group of generated references; determining, based on the algorithmic comparisons, a risk score for a social entity; and determining, based on a statistical algorithm, a confidence score for the risk score, wherein the confidence score indicates the reliability of the determined risk score. 5. The method of claim 1 , further comprising: generating, based on the determined confidence score, a normalized risk score for the social entity. | 0.793608 |
14. The system of claim 12 , wherein it is detected that the user is replying to multiple recipients of the first message, or is replying in the second operation mode, wherein the notification indicates that the message being composed will be sent to multiple recipients of the first message, or will be sent to a recipient that is not the original sender of the first message, or will not be sent to only the sender of the first message. | 14. The system of claim 12 , wherein it is detected that the user is replying to multiple recipients of the first message, or is replying in the second operation mode, wherein the notification indicates that the message being composed will be sent to multiple recipients of the first message, or will be sent to a recipient that is not the original sender of the first message, or will not be sent to only the sender of the first message. 18. The system of claim 14 , wherein the processor is further configured to: provide a user interface object, wherein the user interface object allows the user to change to reply to only the sender of the first message by acting on the user interface object, or to automatically remove multiple recipients of the first message from the recipient list, wherein the user interface object is a button or icon, wherein the user action is a click or a touch on the button or icon. | 0.813295 |
1. A method for database implementation of electronic checklists, the method comprising implementing using at least one processor, the steps of: displaying at a user interface, a first electronic checklist template within a template editor; defining a modified electronic checklist template, wherein defining the modified electronic checklist template comprises modifying the first electronic checklist template based on inputs received at the template editor; and generating a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. | 1. A method for database implementation of electronic checklists, the method comprising implementing using at least one processor, the steps of: displaying at a user interface, a first electronic checklist template within a template editor; defining a modified electronic checklist template, wherein defining the modified electronic checklist template comprises modifying the first electronic checklist template based on inputs received at the template editor; and generating a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. 5. The method according to claim 1 , wherein generating the database implemented electronic checklist template further comprises one or more of for each section defined in the modified electronic checklist template, adding a merged row to the markup language encoded checklist template, and setting content of the merged row to a corresponding section title parsed from the modified electronic checklist template; for each drop down list defined in the modified electronic checklist template, generating a drop down list control object and populating the drop down list control object with corresponding drop down options parsed from the modified electronic checklist template; or selecting a system controlled column for inclusion within the modified electronic checklist template, and associating predefined rules of system behaviour with said system controlled column. | 0.507639 |
19. One or more computer memory storage devices having computer-executable instructions, which when executed perform steps, comprising: in an offline operation before receiving an entity augmentation query corresponding to an entity augmentation task, preprocessing entity attribute relation tables extracted from a corpus into a plurality of indexes used for entity augmentation, including performing holistic matching between the entity attribute relation tables that includes computing values for direct relationships and indirect relationships between at least some of the tables, the indirect relationships determined based upon one or more entity attribute relation tables that have a direct relationship with a query entity; and accessing the plurality of indexes to process the entity augmentation task by identifying a direct relationship between the query entity and a first entity attribute relation table, and an indirect relationship between the first entity attribute relation table and a second entity attribute relation table, identify a first score representing a first match between the query entity and the first entity attribute relation table, and a second score representing a second match between the first entity attribute relation table and the second entity attribute relation table, and determine one or more entity attributes to complete the entity augmentation task, the one or more entity attributes determined based at least partially on the first score and the second score. | 19. One or more computer memory storage devices having computer-executable instructions, which when executed perform steps, comprising: in an offline operation before receiving an entity augmentation query corresponding to an entity augmentation task, preprocessing entity attribute relation tables extracted from a corpus into a plurality of indexes used for entity augmentation, including performing holistic matching between the entity attribute relation tables that includes computing values for direct relationships and indirect relationships between at least some of the tables, the indirect relationships determined based upon one or more entity attribute relation tables that have a direct relationship with a query entity; and accessing the plurality of indexes to process the entity augmentation task by identifying a direct relationship between the query entity and a first entity attribute relation table, and an indirect relationship between the first entity attribute relation table and a second entity attribute relation table, identify a first score representing a first match between the query entity and the first entity attribute relation table, and a second score representing a second match between the first entity attribute relation table and the second entity attribute relation table, and determine one or more entity attributes to complete the entity augmentation task, the one or more entity attributes determined based at least partially on the first score and the second score. 21. The one or more memory storage devices of claim 19 having further computer-executable instructions comprising, receiving the entity augmentation query, the entity augmentation query identifying one or more of an entity set, an attribute name, or an attribute example. | 0.539063 |
1. A method for performing a semantic matching process, the method, with at least one computing device, comprising: detecting one or more meanings of a query, comparing the one or more meanings with one or more detected meanings of one or more pieces of content, and outputting at least one response of the comparing; wherein detecting one or more meanings of the query further comprises: detecting and formalizing all meanings of the query into a global semantic representation, wherein the global semantic representation gives a full meaning of the query by transforming individual or groups of words of the query into semantic representations comprising pairs of lemma and a semantic category retrieved from a lexicon and lexical functions assignments and rules database, and weighting the semantic representations in a basis of their category index and their frequency to generate a global weighted semantic representation of the query; wherein detecting one or more meanings of the one or more pieces of content further comprises: detecting and formalizing one or more meanings of the one or more pieces of content into a global semantic representation, wherein the global semantic representation gives a full meaning of the one or more pieces of content by transforming individual or groups of words of the one or more pieces of content into semantic representations comprising of pairs of lemma and a semantic category retrieved from the lexicon and lexical functions assignments and rules database; and weighting the semantic representations in a basis of their category index and their frequency to generate a global weighted semantic representation of the one or more pieces of content; wherein the comparing further comprises: calculating a semantic matching degree and assigning a score between the global weighted semantic representation of the query and the global weighted semantic representation of the one or more pieces of content, and retrieving at least one piece of content of the one or more pieces of content based on the at least one piece of content having the best assigned score and output the retrieved at least one piece of content as the response; wherein the one or more pieces of content are formed of phrases or expressions obtained from a contents database. | 1. A method for performing a semantic matching process, the method, with at least one computing device, comprising: detecting one or more meanings of a query, comparing the one or more meanings with one or more detected meanings of one or more pieces of content, and outputting at least one response of the comparing; wherein detecting one or more meanings of the query further comprises: detecting and formalizing all meanings of the query into a global semantic representation, wherein the global semantic representation gives a full meaning of the query by transforming individual or groups of words of the query into semantic representations comprising pairs of lemma and a semantic category retrieved from a lexicon and lexical functions assignments and rules database, and weighting the semantic representations in a basis of their category index and their frequency to generate a global weighted semantic representation of the query; wherein detecting one or more meanings of the one or more pieces of content further comprises: detecting and formalizing one or more meanings of the one or more pieces of content into a global semantic representation, wherein the global semantic representation gives a full meaning of the one or more pieces of content by transforming individual or groups of words of the one or more pieces of content into semantic representations comprising of pairs of lemma and a semantic category retrieved from the lexicon and lexical functions assignments and rules database; and weighting the semantic representations in a basis of their category index and their frequency to generate a global weighted semantic representation of the one or more pieces of content; wherein the comparing further comprises: calculating a semantic matching degree and assigning a score between the global weighted semantic representation of the query and the global weighted semantic representation of the one or more pieces of content, and retrieving at least one piece of content of the one or more pieces of content based on the at least one piece of content having the best assigned score and output the retrieved at least one piece of content as the response; wherein the one or more pieces of content are formed of phrases or expressions obtained from a contents database. 4. The method of claim 1 , further comprising, prior to calculating the semantic matching degree: indexing, for each global weighted semantic representation, each single semantic representation, its frequency balanced semantic weight, its semantic approximation factor, and all its expansions allowed by the lexical functions rules, and for each expansion, its semantic approximation factor, of the one or more pieces of content in the contents database. | 0.724316 |
7. A multi-language communication method for making an announcement, under centralized control, concurrently in at least one of a plurality of selectable languages to a plurality of persons, each person having a respective electronically identifiable physical location relative to other of said plurality of persons in a common venue, comprising: providing to each of said persons in said common venue electronic access to a plurality of language options from said centralized control; receiving under said centralized control from each of one or more of said persons in said common venue an electronic indication of a respective choice of language chosen by said respective person from said language options; electronically making said announcement in the form of a public announcement over a public address system in said common venue in a principal language which is a default language of the common venue; and electronically making said announcement available under said centralized control to each person in said common venue who has indicated a language choice in the form of a personal announcement over a respective personal address system in said respective language choice at said respective electronically identifiable physical location in said common venue; whereby a respective person who has chosen a language can access said personal announcement in their respective language choice by means of their respective personal address system at a respective electronically identifiable physical location at least one announcement being on the basis of a real time translation into said respective language of choice. | 7. A multi-language communication method for making an announcement, under centralized control, concurrently in at least one of a plurality of selectable languages to a plurality of persons, each person having a respective electronically identifiable physical location relative to other of said plurality of persons in a common venue, comprising: providing to each of said persons in said common venue electronic access to a plurality of language options from said centralized control; receiving under said centralized control from each of one or more of said persons in said common venue an electronic indication of a respective choice of language chosen by said respective person from said language options; electronically making said announcement in the form of a public announcement over a public address system in said common venue in a principal language which is a default language of the common venue; and electronically making said announcement available under said centralized control to each person in said common venue who has indicated a language choice in the form of a personal announcement over a respective personal address system in said respective language choice at said respective electronically identifiable physical location in said common venue; whereby a respective person who has chosen a language can access said personal announcement in their respective language choice by means of their respective personal address system at a respective electronically identifiable physical location at least one announcement being on the basis of a real time translation into said respective language of choice. 15. The multi-language communication method as claimed in claim 7 , wherein the principal language is selected based on the choices of language of the plurality of persons in the common venue. | 0.59082 |
1. A method for voice transformation, comprising: transforming a source speech of a person using transformation parameters, wherein the transforming comprises modifying the source speech to sound as if the source speech were spoken by a different person; and encoding information on the transformation parameters in an output speech using steganography, wherein the source speech can be reconstructed using the output speech and the information on the transformation parameters, and wherein at least one of the transforming and the encoding is performed by a processor. | 1. A method for voice transformation, comprising: transforming a source speech of a person using transformation parameters, wherein the transforming comprises modifying the source speech to sound as if the source speech were spoken by a different person; and encoding information on the transformation parameters in an output speech using steganography, wherein the source speech can be reconstructed using the output speech and the information on the transformation parameters, and wherein at least one of the transforming and the encoding is performed by a processor. 5. The method as claimed in claim 1 , wherein the information on the transformation parameters includes one of the group of: the transformation parameters, the inverse transformation parameters, compressed or encrypted transformation parameters or inverse transformation parameters, an approximation of the transformation parameters or inverse transformation parameters, a trained set of inverse transformation parameters from a source speech and the transformed speech, an index to remotely stored transformation parameters or inverse transformation parameters. | 0.5 |
1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. | 1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. 9. The method of claim 1 , wherein the selected one or more of the candidate word groups have the greatest determined frequencies among the generated candidate word groups. | 0.558589 |
2. A method as recited in claim 1 , wherein said predicting uses data available to an application other than the speech recognizer. | 2. A method as recited in claim 1 , wherein said predicting uses data available to an application other than the speech recognizer. 26. A method as recited in claim 2 , further comprising storing at least one native pronunciation of the proper noun represented in a first phonetic alphabet specifically for a first language; and wherein said augmenting includes converting a representation of the at least one native pronunciation of the proper noun in the first phonetic alphabet into a second phonetic alphabet specifically for a second language used by the speech recognizer; and adding the at least one native pronunciation as represented in the second phonetic alphabet for use by the speech recognizer. | 0.584034 |
8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. 9. The method of claim 8, further comprising the steps of determining if a run of text being saved to a file and previously identified as using an exception code page uses a code page that is the same as the default code page for said file to which the run of text is being saved; and if not, omitting the specifier for said run of text from the data block of said file so that an exception code page for the run of text is not indicated. | 0.628152 |
10. The method of claim 1 further comprising: attributing information associated with one geographic feature with one of the one or more similar geographic features; and using the attributed information to target content to the similar geographic feature. | 10. The method of claim 1 further comprising: attributing information associated with one geographic feature with one of the one or more similar geographic features; and using the attributed information to target content to the similar geographic feature. 12. The method of claim 10 where the multiple time periods evaluated are the same for each geographic feature. | 0.967198 |
1. A system for machine learning, comprising: a computer; a computer-readable medium having software stored thereon that, when executed by said computer, performs a method comprising the steps of: creating a reference similarity matrix relating a set of reference objects, said similarity matrix containing similarity scores between each reference object and all other reference objects; obtaining a transformation matrix that is the inverse of said reference similarity matrix; creating a query vector relating an unknown object to said set of reference objects using a similarity measure, said query vector containing similarity scores between said unknown object and each of said reference objects; generating an improved query vector using said transformation matrix; and learning which of said reference objects is a best match to said unknown object using said improved query vector. | 1. A system for machine learning, comprising: a computer; a computer-readable medium having software stored thereon that, when executed by said computer, performs a method comprising the steps of: creating a reference similarity matrix relating a set of reference objects, said similarity matrix containing similarity scores between each reference object and all other reference objects; obtaining a transformation matrix that is the inverse of said reference similarity matrix; creating a query vector relating an unknown object to said set of reference objects using a similarity measure, said query vector containing similarity scores between said unknown object and each of said reference objects; generating an improved query vector using said transformation matrix; and learning which of said reference objects is a best match to said unknown object using said improved query vector. 10. The system of claim 1 wherein said reference similarity matrix comprises an identity matrix and a first error matrix. | 0.6375 |
9. In a system including one or more reduced dimensionality indexes to multidimensional data, a method for searching for k records most similar to specified data, using the one or more indexes, the method comprising the steps of: identifying the specified data with a cluster based on clustering information, said cluster being a partition from an original data input set; after said identifying step, reducing a dimensionality of the specified data, based on dimensionality reduction information for an identified cluster; recursively applying said identifying and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; generating dimensionality reduction information for reduced dimensionality specified data, in response to said reducing; and retrieving the .ltoreq.k records most similar to the specified data from the identified cluster using the one or more reduced dimensionality indexes, the dimensionality reduction information and the reduced dimensionality specified data. | 9. In a system including one or more reduced dimensionality indexes to multidimensional data, a method for searching for k records most similar to specified data, using the one or more indexes, the method comprising the steps of: identifying the specified data with a cluster based on clustering information, said cluster being a partition from an original data input set; after said identifying step, reducing a dimensionality of the specified data, based on dimensionality reduction information for an identified cluster; recursively applying said identifying and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; generating dimensionality reduction information for reduced dimensionality specified data, in response to said reducing; and retrieving the .ltoreq.k records most similar to the specified data from the identified cluster using the one or more reduced dimensionality indexes, the dimensionality reduction information and the reduced dimensionality specified data. 17. The method of claim 9, further comprising the steps of: searching for candidate terminal clusters that can contain one or more of the k records most similar to the specified data at each level of the hierarchy of reduced dimensionality clusters starting from a terminal cluster at a lowest level of said hierarchy to which the specified data belongs; and for each candidate terminal cluster, performing an intra-cluster search for the k records most similar to the specified data. | 0.636917 |
1. A computer system for storage and retrieval of data in extensible markup language (XML) documents, comprising: a memory; and a processor operatively coupled to the memory and configured to execute computer executable program modules, including: an import manager module configured to convert at least one file format to XML code defined by an XML schema; an indexer module configured to encode document data comprised in the XML code defined by the XML schema into a binary data structure, comprising: a scoping submodule configured to determine scope within the document data and the scope comprises at least one well-formed fragment of the XML code; and a storage submodule configured to store the binary data structure by the scope; a lexicon module configured to store at least one token and at least one token type and assigning at least one token identifier number, wherein said token includes data elements corresponding to XML syntax and said at least one token type reflects at least one component of XML syntax; a sequence module configured to store said at least one token identifier number in an original sequence; a determination module configured to determine whether said token is included in a lexicon; a token identifier number retrieval module configured to retrieve said token identifier number from said lexicon if said token is included in said lexicon, appending said token identifier number to said original sequence, and storing said token identifier number in the list for the XML data element; a lexicon storage module configured to store said token and said token type in the lexicon if said token is not included in said lexicon, assigning a unique token identifier to said token, appending said token identifier to the original sequence, and storing said token identifier in the list for the XML data element; a postings module configured to map said at least one token identifier number to a position of said token identifier number in said original sequence, wherein the postings module further inverts the position information from a list of tokens in an XML data element to map at least one selected token to all the XML data elements in which the selected token appears; a regenerator module configured to retrieve said at least one token for the scope in said original sequence, comprising: an insertion submodule configured to insert the at least one token into an output stream for each such well-formed fragment of the XML code; and a return submodule configured to return completed XML markup upon reading an end of the scope; a XML grammar state machine module configured to use token type information to compute the XML syntax for regenerating the XML code, comprising: a reading submodule configured to read the next token identifier number from the original sequence; a retrieval submodule configured to retrieve the token and token type for a token identifier number from the lexicon; and a token insertion submodule configured to insert said token into the output stream with the XML markup syntax appropriate for type. | 1. A computer system for storage and retrieval of data in extensible markup language (XML) documents, comprising: a memory; and a processor operatively coupled to the memory and configured to execute computer executable program modules, including: an import manager module configured to convert at least one file format to XML code defined by an XML schema; an indexer module configured to encode document data comprised in the XML code defined by the XML schema into a binary data structure, comprising: a scoping submodule configured to determine scope within the document data and the scope comprises at least one well-formed fragment of the XML code; and a storage submodule configured to store the binary data structure by the scope; a lexicon module configured to store at least one token and at least one token type and assigning at least one token identifier number, wherein said token includes data elements corresponding to XML syntax and said at least one token type reflects at least one component of XML syntax; a sequence module configured to store said at least one token identifier number in an original sequence; a determination module configured to determine whether said token is included in a lexicon; a token identifier number retrieval module configured to retrieve said token identifier number from said lexicon if said token is included in said lexicon, appending said token identifier number to said original sequence, and storing said token identifier number in the list for the XML data element; a lexicon storage module configured to store said token and said token type in the lexicon if said token is not included in said lexicon, assigning a unique token identifier to said token, appending said token identifier to the original sequence, and storing said token identifier in the list for the XML data element; a postings module configured to map said at least one token identifier number to a position of said token identifier number in said original sequence, wherein the postings module further inverts the position information from a list of tokens in an XML data element to map at least one selected token to all the XML data elements in which the selected token appears; a regenerator module configured to retrieve said at least one token for the scope in said original sequence, comprising: an insertion submodule configured to insert the at least one token into an output stream for each such well-formed fragment of the XML code; and a return submodule configured to return completed XML markup upon reading an end of the scope; a XML grammar state machine module configured to use token type information to compute the XML syntax for regenerating the XML code, comprising: a reading submodule configured to read the next token identifier number from the original sequence; a retrieval submodule configured to retrieve the token and token type for a token identifier number from the lexicon; and a token insertion submodule configured to insert said token into the output stream with the XML markup syntax appropriate for type. 4. The computer system according to claim 1 , wherein converting at least one file format to XML code is performed by at least one filter, wherein said at least one filter comprises at least one shared dynamically linked library. | 0.517032 |
8. A device comprising: one or more processors to: obtain data in a first format, the data including first information associated with a first information type and second information associated with a second information type, and the second information type being different from the first information type; receive, from a user, information defining one or more translation rules for converting the data to a second format that is different from the first format; apply the one or more translation rules to the first information type and to the second information type, the one or more translation rules affecting the first information type differently than the second information type; determine that the first information is incompatible with the second format; apply a first visual style to the first information to modify a display of the first information, the first visual style indicating that the first information is incompatible with the second format, and a second visual style being applied to the second information to modify a display of the second information, the second visual style providing the second information for display in the second format in conjunction with providing the second information for display in the first format; and provide information associated with the first information being incompatible with the second format. | 8. A device comprising: one or more processors to: obtain data in a first format, the data including first information associated with a first information type and second information associated with a second information type, and the second information type being different from the first information type; receive, from a user, information defining one or more translation rules for converting the data to a second format that is different from the first format; apply the one or more translation rules to the first information type and to the second information type, the one or more translation rules affecting the first information type differently than the second information type; determine that the first information is incompatible with the second format; apply a first visual style to the first information to modify a display of the first information, the first visual style indicating that the first information is incompatible with the second format, and a second visual style being applied to the second information to modify a display of the second information, the second visual style providing the second information for display in the second format in conjunction with providing the second information for display in the first format; and provide information associated with the first information being incompatible with the second format. 10. The device of claim 8 , where the one or more processors are further to: generate code based on the one or more translation rules, where the code includes elements corresponding to an application of the one or more translation rules; receive additional data to be converted from the first format to the second format; and use the code to convert the additional data from the first format to the second format. | 0.678085 |
4. The method of claim 1 wherein the cost of computing the query is the weighted sum of an estimated CPU cost and an estimated I/O cost. | 4. The method of claim 1 wherein the cost of computing the query is the weighted sum of an estimated CPU cost and an estimated I/O cost. 5. The method of claim 4 wherein said estimated CPU cost is computed with an input size of data to be queried, a size of the output from the query and a plurality of factors specific to an implementation of the database system. | 0.904523 |
31. The computer-readable medium of claim 27 , wherein determining the weighted overall quality of result statistic comprises: determining a respective difference score for each of the plurality of versions of the document with reference to the reference version of the document, wherein the difference score for a particular version in the plurality of versions of the document and the reference version of the document measures a difference between a representation of the particular version and a representation of the reference version of the document; and weighting each version-specific quality of result statistic by a weight derived from the difference score for the version of the document associated with the version-specific quality of result statistic. | 31. The computer-readable medium of claim 27 , wherein determining the weighted overall quality of result statistic comprises: determining a respective difference score for each of the plurality of versions of the document with reference to the reference version of the document, wherein the difference score for a particular version in the plurality of versions of the document and the reference version of the document measures a difference between a representation of the particular version and a representation of the reference version of the document; and weighting each version-specific quality of result statistic by a weight derived from the difference score for the version of the document associated with the version-specific quality of result statistic. 38. The computer-readable medium of claim 31 , wherein the difference score is determined as an inverse of a similarity score, where the similarity score is defined as similarity ( A , B ) = S ( A ) ⋂ S ( B ) S ( A ) , where A is the particular version of the document and B is the reference version of the document. | 0.829352 |
14. A computer-readable storage medium storing instructions that, when executed by a processor, perform operation comprising: receiving a first request for information corresponding to first electronic content being rendered to a user submitting the first request when the first request is submitted; deriving context information associated with the first request based on the first electronic content being rendered to the user when the first request is submitted; in response to deriving the context information, storing the context information; receiving a second request, at a time subsequent to the first request, for information corresponding to second electronic content; in response to receiving the second request, determining whether the stored context information is relevant to the second request; in response to a determination that the stored context information is relevant to the second request: accessing, from electronic storage, the stored context information derived based on the first electronic content rendered during the first request; and causing presentation, to a user submitting the second request, of the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request. | 14. A computer-readable storage medium storing instructions that, when executed by a processor, perform operation comprising: receiving a first request for information corresponding to first electronic content being rendered to a user submitting the first request when the first request is submitted; deriving context information associated with the first request based on the first electronic content being rendered to the user when the first request is submitted; in response to deriving the context information, storing the context information; receiving a second request, at a time subsequent to the first request, for information corresponding to second electronic content; in response to receiving the second request, determining whether the stored context information is relevant to the second request; in response to a determination that the stored context information is relevant to the second request: accessing, from electronic storage, the stored context information derived based on the first electronic content rendered during the first request; and causing presentation, to a user submitting the second request, of the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request. 16. The computer-readable storage medium of claim 14 wherein receiving the first request and receiving the second request comprises receiving the first request and the second request from a single party, further comprising: identifying a target community associated with the single party; and based on the identified target community, selecting the information satisfying the second request from among multiple information options. | 0.52291 |
1. A method of creating a graphical user interface for search results, the method comprising: identifying search results for a received query from potential search results based on content data generated based on analyzing the potential search results, the identified search results including a first identified search result associated with a first link to first content and a second search identified result associated with a second link to second content; accessing characteristic data generated for the first and second identified search results based on analyzing the potential search results; determining, based on the accessed characteristic data corresponding to the first identified search result, a first property associated with an ability to access the first content using the first link; determining, based on the accessed characteristic data corresponding to the second identified search result, a second property associated with an ability to access the second content using the second link, the second property being different than the first property and indicating that the ability to access the second content using the second link is different than the ability to access the first content using the first link; and creating a graphical user interface enabling display of the identified search results to the user, the graphical user interface providing a perceivable indication, appended to an end of each search result, that (i) the ability to access the second content using the second link is different than the ability to access the first content using the first link and that (ii) includes prose and a selectable icon, wherein, when an icon is selected, the icon reveals a description of (i) at least one characteristic of a search result, (ii) an explanation of the icon, and (iii) a detailed description of the characteristic and how a determination was made that content for which the icon is displayed has the at least one characteristic represented by the icon. | 1. A method of creating a graphical user interface for search results, the method comprising: identifying search results for a received query from potential search results based on content data generated based on analyzing the potential search results, the identified search results including a first identified search result associated with a first link to first content and a second search identified result associated with a second link to second content; accessing characteristic data generated for the first and second identified search results based on analyzing the potential search results; determining, based on the accessed characteristic data corresponding to the first identified search result, a first property associated with an ability to access the first content using the first link; determining, based on the accessed characteristic data corresponding to the second identified search result, a second property associated with an ability to access the second content using the second link, the second property being different than the first property and indicating that the ability to access the second content using the second link is different than the ability to access the first content using the first link; and creating a graphical user interface enabling display of the identified search results to the user, the graphical user interface providing a perceivable indication, appended to an end of each search result, that (i) the ability to access the second content using the second link is different than the ability to access the first content using the first link and that (ii) includes prose and a selectable icon, wherein, when an icon is selected, the icon reveals a description of (i) at least one characteristic of a search result, (ii) an explanation of the icon, and (iii) a detailed description of the characteristic and how a determination was made that content for which the icon is displayed has the at least one characteristic represented by the icon. 2. The method of claim 1 wherein: determining, based on the accessed characteristic data corresponding to the first identified search result, the first property associated with the ability to access the first content using the first link comprises determining that the first content is currently available through invocation of the first link; determining, based on the accessed characteristic data corresponding to the second identified search result, the second property associated with the ability to access the second content using the second link comprises determining that the second content is currently unavailable through invocation of the second link; and creating the graphical user interface enabling display of the identified search results to the user, the graphical user interface providing the perceivable indication that the ability to access the second content using the second link is different than the ability to access the first content using the first link comprises creating a graphical user interface enabling display of the identified search results to the user, the graphical user interface providing a perceivable indication that the second content is currently unavailable through invocation of the second link. | 0.646913 |
3. The system of claim 1 , wherein the operations further include facilitating execution of a background search in connection with interaction between the user and an entity of the entities of the social network. | 3. The system of claim 1 , wherein the operations further include facilitating execution of a background search in connection with interaction between the user and an entity of the entities of the social network. 4. The system of claim 3 , wherein the interaction comprises an instant messaging session. | 0.978906 |
2. The method of claim 1 wherein: the annotation comprises a user specified status indication; wherein determining a policy follow up action based upon the annotation of indications of success and failure further comprises determining a policy follow up action based upon the user specified indication. | 2. The method of claim 1 wherein: the annotation comprises a user specified status indication; wherein determining a policy follow up action based upon the annotation of indications of success and failure further comprises determining a policy follow up action based upon the user specified indication. 3. The method of claim 2 wherein determining a policy follow up action based upon the annotation of indications of success and failure further comprises: comparing the user specified status indication against the annotation of the function template. | 0.923678 |
1. An apparatus for letter recognition in a terminal equipped with a touch screen, comprising: a user interface having a plurality of letter input areas displayed on the touch screen, the plurality of letter input areas each having a pair of first language consonant letters comprising a basic consonant letter and an extended consonant letter, wherein each extended consonant letter has a form similar to a corresponding basic consonant letter, and wherein the basic consonant letters and the extended consonant letters of the first language are mapped and assigned to basic consonant letters and extended consonant letters of a second language; and a controller for selecting one of the consonant letters assigned to a letter input area corresponding to a touch pen input type and enabling display of the selected consonant letter. | 1. An apparatus for letter recognition in a terminal equipped with a touch screen, comprising: a user interface having a plurality of letter input areas displayed on the touch screen, the plurality of letter input areas each having a pair of first language consonant letters comprising a basic consonant letter and an extended consonant letter, wherein each extended consonant letter has a form similar to a corresponding basic consonant letter, and wherein the basic consonant letters and the extended consonant letters of the first language are mapped and assigned to basic consonant letters and extended consonant letters of a second language; and a controller for selecting one of the consonant letters assigned to a letter input area corresponding to a touch pen input type and enabling display of the selected consonant letter. 2. The apparatus as set forth in claim 1 , wherein the controller enables display of a basic consonant letter of the first language assigned to a corresponding letter input area when the touch pen input type is a pen click. | 0.67621 |
16. A system comprising: a first device, including: a microphone to generate an audio signal representative of an utterance of a user, the utterance comprising a query to present information; a speaker; one or more first processors; and one or more first computer-readable media storing first computer-executable instructions that, when executed by the one or more first processors, cause the one or more first processors to perform acts comprising: determining, based at least in part on the utterance, a second device proximate to the first device, the first device and the second device coupled to a same wireless network; causing the speaker to output audio content associated with the utterance of the user, the audio content including at least an identity of the second device; and causing the information to be provided to the second device, the information relating to the utterance of the user; and the second device including: a presentation component configured to present content associated with the information; an application configured to receive instructions for presentation of the content; one or more second processors; and one or more second computer-readable media storing second computer-executable instructions that, when executed by the one or more second processors, cause the one or more second processors to perform acts comprising: presenting the content associated with the utterance of the user using the presentation component. | 16. A system comprising: a first device, including: a microphone to generate an audio signal representative of an utterance of a user, the utterance comprising a query to present information; a speaker; one or more first processors; and one or more first computer-readable media storing first computer-executable instructions that, when executed by the one or more first processors, cause the one or more first processors to perform acts comprising: determining, based at least in part on the utterance, a second device proximate to the first device, the first device and the second device coupled to a same wireless network; causing the speaker to output audio content associated with the utterance of the user, the audio content including at least an identity of the second device; and causing the information to be provided to the second device, the information relating to the utterance of the user; and the second device including: a presentation component configured to present content associated with the information; an application configured to receive instructions for presentation of the content; one or more second processors; and one or more second computer-readable media storing second computer-executable instructions that, when executed by the one or more second processors, cause the one or more second processors to perform acts comprising: presenting the content associated with the utterance of the user using the presentation component. 22. The system as recited in claim 16 , further comprising: a third device, remote from the first device and the second device, the third device configured to receive the information from the first device; identify the content based at least in part on the information; and provide the content to the second device for presentation. | 0.5 |
15. A method according to claim 14 , further comprising: selecting a median value and edge conditions for the total frequency occurrences of the terms; and generating the subset of documents from those documents in the set that satisfy the edge conditions. | 15. A method according to claim 14 , further comprising: selecting a median value and edge conditions for the total frequency occurrences of the terms; and generating the subset of documents from those documents in the set that satisfy the edge conditions. 16. A method according to claim 15 , further comprising: re-centering the median value; and generating a different subset of documents for grouping. | 0.877455 |
1. A computer language translation system for converting a first Object-Oriented Programming (OOP) computer language source code to a second OOP computer language source code, the system comprising: a computer having a storage, said computer having software executing thereon and including: a translation module having specific language knowledge of the first and second OOP computer languages; an emulated Application Programming Interface (API) library module to facilitate mapping of functions in the first and second OOP computer languages, said API library having: data indicative of types of data manipulations of the first OOP computer language source code; second computer language API equivalent functions callable by said second computer language; said translation module utilizing the specific language knowledge and said API library and correlating the type of data manipulation the first OOP computer language source code performs to second OOP computer language source code; and a generation module generating second OOP computer language source code. | 1. A computer language translation system for converting a first Object-Oriented Programming (OOP) computer language source code to a second OOP computer language source code, the system comprising: a computer having a storage, said computer having software executing thereon and including: a translation module having specific language knowledge of the first and second OOP computer languages; an emulated Application Programming Interface (API) library module to facilitate mapping of functions in the first and second OOP computer languages, said API library having: data indicative of types of data manipulations of the first OOP computer language source code; second computer language API equivalent functions callable by said second computer language; said translation module utilizing the specific language knowledge and said API library and correlating the type of data manipulation the first OOP computer language source code performs to second OOP computer language source code; and a generation module generating second OOP computer language source code. 5. The system according to claim 1 wherein the first computer language source code comprises a class. | 0.646552 |
13. The computer program product of claim 9 , wherein the contextual information is client-specific. | 13. The computer program product of claim 9 , wherein the contextual information is client-specific. 14. The computer program product of claim 13 , wherein the contextual information comprises a client identifier that identifies which version of the versioned data object should be retrieved by a particular client. | 0.94707 |
1. A method of database replication, the method comprising: detecting, by one or more processor of a machine, a request for provision of a first document that is available for provision; updating a count of referrals upon detecting a request sent from a set of one or more networks for provision of the first document; generating a second document based on the first document, the second document being a substitute for the first document subsequent to the first document becoming unavailable for provision, the generating of the second document being responsive to a determination that the updated count of referrals has transgressed a predetermined threshold value, the generating of the second document being performed by one or more processor of the machine; and providing the second document in lieu of the first document when the first document is requested subsequent to the first document becoming unavailable upon expiration of a predetermined time of availability of the first document. | 1. A method of database replication, the method comprising: detecting, by one or more processor of a machine, a request for provision of a first document that is available for provision; updating a count of referrals upon detecting a request sent from a set of one or more networks for provision of the first document; generating a second document based on the first document, the second document being a substitute for the first document subsequent to the first document becoming unavailable for provision, the generating of the second document being responsive to a determination that the updated count of referrals has transgressed a predetermined threshold value, the generating of the second document being performed by one or more processor of the machine; and providing the second document in lieu of the first document when the first document is requested subsequent to the first document becoming unavailable upon expiration of a predetermined time of availability of the first document. 2. The method of claim 1 , wherein the first document includes an identifier of a network that referred the request. | 0.657307 |
19. A method of generating an event message enabling determination of a correlation among events occurring in one or more network elements, wherein the correlation among the events results from a propagation of a root event through communication entities of the one or more network elements, the method being carried out in a network element and comprising: detecting occurrence of an event in a first communication entity of the network element, wherein the events comprise at least one of alarm events and performance events, and wherein the performance events comprise at least one of a counter and a key performance indicator; determining one or more context identifiers describing an internal communication state of the first communication entity at the time when the event occurred; generating the event message configured to signal two or more of the context identifiers pertaining to different communication entities involved in the event; and reporting the event message towards a central network management entity, wherein each context identifier comprises a first parameter indicative of a context type and a second parameter indicative of an associated identification value, and wherein two events are determined to be correlated when event messages associated with the two events: (i) comprise at least one of the context identifiers of the same context type; and (ii) have the same identification value. | 19. A method of generating an event message enabling determination of a correlation among events occurring in one or more network elements, wherein the correlation among the events results from a propagation of a root event through communication entities of the one or more network elements, the method being carried out in a network element and comprising: detecting occurrence of an event in a first communication entity of the network element, wherein the events comprise at least one of alarm events and performance events, and wherein the performance events comprise at least one of a counter and a key performance indicator; determining one or more context identifiers describing an internal communication state of the first communication entity at the time when the event occurred; generating the event message configured to signal two or more of the context identifiers pertaining to different communication entities involved in the event; and reporting the event message towards a central network management entity, wherein each context identifier comprises a first parameter indicative of a context type and a second parameter indicative of an associated identification value, and wherein two events are determined to be correlated when event messages associated with the two events: (i) comprise at least one of the context identifiers of the same context type; and (ii) have the same identification value. 20. The method of claim 19 , wherein the two or more context identifiers include at least one first context identifier relating to the first communication entity of the reporting network element and at least one second context identifier relating to a second communication entity of a network element on a peer side of the reporting network element, and wherein information regarding the second context identifier relating to the peer side has been obtained by the reporting network element during: at least one of a context setup process and a configuration process from the central network management entity; or a context exchange process from the network element on the peer side. | 0.539778 |
1. A method for facilitating communications for a user transaction, the method comprising, by a processor and associated memory: determining a goal transaction for a user to provide input to a human-to-machine interface, said determining including analyzing the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface and accounting for at least a subset of the states and associating the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; constructing and presenting the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and enabling a user interaction with the human-to-machine interface via the visual representation. | 1. A method for facilitating communications for a user transaction, the method comprising, by a processor and associated memory: determining a goal transaction for a user to provide input to a human-to-machine interface, said determining including analyzing the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface and accounting for at least a subset of the states and associating the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; constructing and presenting the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and enabling a user interaction with the human-to-machine interface via the visual representation. 5. The method of claim 1 wherein determining the goal transaction of the user includes determining pending action items requiring user input. | 0.625445 |
20. A non-transitory computer-readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to perform operations comprising: wrapping, by the processing device, text in a markup language file with directives of a web server type page; identifying an internal link in the markup language file using regular expression pattern matching, the internal link comprising a markup language extension; converting, by the processing device, the internal link into a web server type page link by replacing the markup language extension with a web server type page extension. | 20. A non-transitory computer-readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to perform operations comprising: wrapping, by the processing device, text in a markup language file with directives of a web server type page; identifying an internal link in the markup language file using regular expression pattern matching, the internal link comprising a markup language extension; converting, by the processing device, the internal link into a web server type page link by replacing the markup language extension with a web server type page extension. 21. The non-transitory computer-readable medium of claim 20 , wherein the markup language is hypertext markup language (HTML). | 0.659091 |
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