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9,679,061 | 12 | 15 | 12. An apparatus that collects and uploads implicit analytic data, the apparatus comprising: a controller configured to control operations of the apparatus and configured to collect implicit event data corresponding to implicit events generated by a user; a memory coupled to the controller, the memory configured to store dependency rules that correspond explicit events to implicit event data; a user interface configured to receive an explicit event generated by the user; a device activity manager coupled to the controller, the device activity manager configured to: evaluate dependency rules determined from historical usage of the apparatus and corresponding to the explicit event, identify a relevant subset of the implicit event data corresponding to the explicit event based on evaluating the dependency rules, and determine a high probability that a select subset of implicit event data corresponds to the explicit event based on the historical usage of the apparatus; and a transceiver configured to upload, from the apparatus, the relevant subset of the implicit event data and upload explicit event data corresponding to the explicit event, and wherein the device activity manager is further configured to defer the uploading of the select subset of the implicit event data in response to determining a high probability of a select subset of implicit event data corresponding to the explicit event. | 12. An apparatus that collects and uploads implicit analytic data, the apparatus comprising: a controller configured to control operations of the apparatus and configured to collect implicit event data corresponding to implicit events generated by a user; a memory coupled to the controller, the memory configured to store dependency rules that correspond explicit events to implicit event data; a user interface configured to receive an explicit event generated by the user; a device activity manager coupled to the controller, the device activity manager configured to: evaluate dependency rules determined from historical usage of the apparatus and corresponding to the explicit event, identify a relevant subset of the implicit event data corresponding to the explicit event based on evaluating the dependency rules, and determine a high probability that a select subset of implicit event data corresponds to the explicit event based on the historical usage of the apparatus; and a transceiver configured to upload, from the apparatus, the relevant subset of the implicit event data and upload explicit event data corresponding to the explicit event, and wherein the device activity manager is further configured to defer the uploading of the select subset of the implicit event data in response to determining a high probability of a select subset of implicit event data corresponding to the explicit event. 15. The apparatus according to claim 12 , wherein the dependency rules are determined over a plurality of devices associated with a user of the apparatus. | 0.729825 |
4,751,737 | 18 | 19 | 18. In a speech recognition system, wherein speech is represented by data in frames of equal time intervals, an arrangement for generating a final word template from a plurality of tokens, including: (a) means for forming an interim template representative of at least one token; (b) means for generating a time alignment path between said interim template and an additional token; (c) means for mapping frames from said interim template and said additional token along said time alignment path onto an averaged time axis; and (d) means for combining data associated with said mapped frames to produce composite frames representative of a final word template. | 18. In a speech recognition system, wherein speech is represented by data in frames of equal time intervals, an arrangement for generating a final word template from a plurality of tokens, including: (a) means for forming an interim template representative of at least one token; (b) means for generating a time alignment path between said interim template and an additional token; (c) means for mapping frames from said interim template and said additional token along said time alignment path onto an averaged time axis; and (d) means for combining data associated with said mapped frames to produce composite frames representative of a final word template. 19. An arrangement, according to claim 18, further comprising means for normalizing an accumulation of combined data to form said composite frames. | 0.854167 |
7,680,862 | 17 | 18 | 17. The method set forth in claim 14 wherein the method further comprises the steps of: providing an indication when it is not possible to produce the SQL string; and responding to the indication by not performing the step of rewriting the SQL statement. | 17. The method set forth in claim 14 wherein the method further comprises the steps of: providing an indication when it is not possible to produce the SQL string; and responding to the indication by not performing the step of rewriting the SQL statement. 18. The method set forth in claim 17 further comprising the step of: executing the table function when the SQL statement is executed. | 0.934289 |
10,007,648 | 9 | 10 | 9. The method according to claim 1 , further comprising: preparing a message file associated with the program product, wherein the message file includes at least a set of the character strings of the user-interface of the program product and respective identifiers within the message file that is uniquely associated with the character string. | 9. The method according to claim 1 , further comprising: preparing a message file associated with the program product, wherein the message file includes at least a set of the character strings of the user-interface of the program product and respective identifiers within the message file that is uniquely associated with the character string. 10. The method according to claim 9 , further comprising: preparing a master table, wherein the master table includes at least a set of the identifiers within the message file and the master identifiers uniquely associated with the identifier within the message file. | 0.950556 |
8,260,785 | 1 | 10 | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. 10. The method of claim 1 , wherein the one or more predefined criteria are met when a predetermined number of facts in the fact repository have been modified. | 0.883431 |
7,900,174 | 1 | 6 | 1. A method for characterizing an integrated circuit design, the method comprising: receiving a description of one or more leaf cells; describing the integrated circuit design in a high-level language using the description of the one or more leaf cells and using a computer, wherein the description of the integrated circuit design includes specifying placement of the one or more leaf cells, and specifying connectivity between the one or more leaf cells; developing a physical layout design based on the high-level language description; extracting a critical path of the physical layout design; extracting a circuit netlist file based on the extracted critical path; defining instructions in the high-level language to perform one or more simulations on the circuit netlist file; performing the one or more simulations on the circuit netlist file, wherein the one or more simulations are performed to determine one or more values for one or more design parameters; and providing the one or more values for the one or more design parameters in a pre-defined output format based on the one or more simulations. | 1. A method for characterizing an integrated circuit design, the method comprising: receiving a description of one or more leaf cells; describing the integrated circuit design in a high-level language using the description of the one or more leaf cells and using a computer, wherein the description of the integrated circuit design includes specifying placement of the one or more leaf cells, and specifying connectivity between the one or more leaf cells; developing a physical layout design based on the high-level language description; extracting a critical path of the physical layout design; extracting a circuit netlist file based on the extracted critical path; defining instructions in the high-level language to perform one or more simulations on the circuit netlist file; performing the one or more simulations on the circuit netlist file, wherein the one or more simulations are performed to determine one or more values for one or more design parameters; and providing the one or more values for the one or more design parameters in a pre-defined output format based on the one or more simulations. 6. The method according to claim 1 , wherein the instructions are defined using a Graphical User Interface (GUI). | 0.874723 |
8,693,644 | 8 | 14 | 8. A call center system comprising: a call handler configured to process a call between a remote party and an agent, the call handler comprising a first processor configured to receive an event notification signifying detection of a first keyword spoken by the remote party, and present information in response to receiving the event notification on a computer screen used by the agent for commanding a pre-recorded response in a voice of the agent to be played to the remote party; and a speech analytics component comprising a second processor configured to analyze speech from the remote party to detect a presence of the first keyword, and provide the event notification to the call handler signifying detection of the first keyword spoken by the remote party. | 8. A call center system comprising: a call handler configured to process a call between a remote party and an agent, the call handler comprising a first processor configured to receive an event notification signifying detection of a first keyword spoken by the remote party, and present information in response to receiving the event notification on a computer screen used by the agent for commanding a pre-recorded response in a voice of the agent to be played to the remote party; and a speech analytics component comprising a second processor configured to analyze speech from the remote party to detect a presence of the first keyword, and provide the event notification to the call handler signifying detection of the first keyword spoken by the remote party. 14. The call center system of claim 8 , wherein the first processor is further configured to: receive a command from the agent to play the pre-recorded response to the remote party; and play the pre-recorded response to the remote party in response to receiving the command. | 0.661728 |
7,505,894 | 16 | 19 | 16. The system of claim 15 wherein each of the nodes in the target language dependency tree represent a word in a target language text fragment, and wherein the order model is configured to assign a score to an order for each node, in turn, at each level of the target language dependency tree. | 16. The system of claim 15 wherein each of the nodes in the target language dependency tree represent a word in a target language text fragment, and wherein the order model is configured to assign a score to an order for each node, in turn, at each level of the target language dependency tree. 19. The system of claim 16 wherein the order model is configured to compute a probability of a position of each node having a position relative to other nodes at a same level of the target language dependency tree. | 0.93562 |
9,626,368 | 9 | 15 | 9. A computer program product for merging documents comprising: a computer readable storage device having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: receive an update document and a target document, wherein the update document and target document are document instances of a common document schema; determine whether an item of information in the update document is associated with an eligible path of the document schema in a predefined update table; generate, responsive to affirming that the item of information is associated with the eligible path, a specification of an operation by which the item of information is merged into the target document in compliance with the document schema; and apply the specified operation to the target document to produce an updated document in compliance with the document schema. | 9. A computer program product for merging documents comprising: a computer readable storage device having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: receive an update document and a target document, wherein the update document and target document are document instances of a common document schema; determine whether an item of information in the update document is associated with an eligible path of the document schema in a predefined update table; generate, responsive to affirming that the item of information is associated with the eligible path, a specification of an operation by which the item of information is merged into the target document in compliance with the document schema; and apply the specified operation to the target document to produce an updated document in compliance with the document schema. 15. The computer program product of claim 9 , wherein the specification of an operation comprises a selected one of an XQuery expression and an XSLT expression. | 0.88218 |
9,858,051 | 16 | 17 | 16. The method of claim 15 wherein determining the transitions includes determining the transition DFA state from the marked DFA state for the character of the alphabet recognized by the NFA graph. | 16. The method of claim 15 wherein determining the transitions includes determining the transition DFA state from the marked DFA state for the character of the alphabet recognized by the NFA graph. 17. The method of claim 16 wherein determining the transition DFA state includes: computing the second hash value for the transitions of the one or more NFA states of the NFA graph; and comparing the second hash value to the hash value entries in the EC cache table. | 0.9266 |
7,853,475 | 1 | 2 | 1. A method of advertising to a remote unit belonging to a user group of remote units, the method comprising: identifying, by the remote unit, a context associated with a communication sent to or received by the remote unit belonging to the user group of remote units; determining, on a server, whether the identified context is associated with one or more advertisements by querying correlation data to identify advertisements having context that correlates to the identified context; and when the identified context is associated with one or more advertisements, transmitting, by the server, the one or more advertisements to at least one remote unit belonging to the user group wherein transmitting the one or more advertisements comprises transmitting the one or more advertisements to at least one remote unit belonging to the user group that did not send or receive a communication containing the identified context. | 1. A method of advertising to a remote unit belonging to a user group of remote units, the method comprising: identifying, by the remote unit, a context associated with a communication sent to or received by the remote unit belonging to the user group of remote units; determining, on a server, whether the identified context is associated with one or more advertisements by querying correlation data to identify advertisements having context that correlates to the identified context; and when the identified context is associated with one or more advertisements, transmitting, by the server, the one or more advertisements to at least one remote unit belonging to the user group wherein transmitting the one or more advertisements comprises transmitting the one or more advertisements to at least one remote unit belonging to the user group that did not send or receive a communication containing the identified context. 2. The method of claim 1 wherein before determining whether the identified context is associated with one or more advertisements, the method comprises: determining, by the server, whether the identified context is contained in a context index; when the identified context is not contained in the context index, determining, by the server, whether the identified context is contained in a candidate list; and when the identified context is not contained in the candidate list, adding, by the server, the identified context to the candidate list. | 0.500917 |
8,065,605 | 20 | 22 | 20. A computer program product, tangibly stored on a machine readable medium, for indexing structured documents, comprising instructions operable to cause a server computer to: apply a pre-defined rule set to each indexable document in a plurality of structured documents, including instructions operable to cause the server computer to apply the pre-defined rule set to a plurality of versions of an indexable document in the plurality of structured documents, to extract one or more index values, the pre-defined rule set including a plurality of rules, each rule having a distinct rule identifier, each extracted index value being extracted by a rule in the pre-defined rule set, wherein one or more versions of the indexable document is concurrently accessible to a plurality of users for collaborative authoring; and for each extracted index value, store in an index-value data structure the extracted index-value, the rule identifier of the rule that extracted the index value, and information identifying the respective indexable document and a respective version of the respective indexable document from which the index-value was extracted. | 20. A computer program product, tangibly stored on a machine readable medium, for indexing structured documents, comprising instructions operable to cause a server computer to: apply a pre-defined rule set to each indexable document in a plurality of structured documents, including instructions operable to cause the server computer to apply the pre-defined rule set to a plurality of versions of an indexable document in the plurality of structured documents, to extract one or more index values, the pre-defined rule set including a plurality of rules, each rule having a distinct rule identifier, each extracted index value being extracted by a rule in the pre-defined rule set, wherein one or more versions of the indexable document is concurrently accessible to a plurality of users for collaborative authoring; and for each extracted index value, store in an index-value data structure the extracted index-value, the rule identifier of the rule that extracted the index value, and information identifying the respective indexable document and a respective version of the respective indexable document from which the index-value was extracted. 22. The computer program product of claim 20 , wherein the plurality of structured documents are included in a WebDAV file system. | 0.831606 |
8,838,451 | 8 | 9 | 8. The method of claim 1 wherein automatically forming a musical composition further comprises: combining the musical composition of selected musical phrases with a pre-composed musical composition having the same predetermined meter. | 8. The method of claim 1 wherein automatically forming a musical composition further comprises: combining the musical composition of selected musical phrases with a pre-composed musical composition having the same predetermined meter. 9. The method of claim 8 wherein the pre-composed musical composition having the same predetermined meter is at least partially repeated during the formed musical composition. | 0.879973 |
8,762,326 | 10 | 11 | 10. A server device, of a topic ranking system, comprising: a memory to store: a user profile data structure that includes information about multiple users, and a topic data structure that includes topics, where each topic is assigned a popularity score; and a processor to execute instructions to: receive a request from a client device associated with a user, obtain, from the topic data structure, a list of popular topics for a particular time period, a ranking score for each topic in the list of popular topics, and a topic profile for a particular topic in the list of popular topics, identify a user profile for the user, determine a personalization score for the particular topic in the list of popular topics, where the personalization score for the particular topic is based on one or more similarities between the user profile and the topic profile for the particular topic, the processor, when determining the personalization score, being further to: represent the user profile as a first component that represents the user's interest in different subject matter categories, represent the topic profile as a second component that represents a relevance of the particular topic to the different subject matter categories, apply a vector similarity function to the first component and the second component to compute a similarity score for the first component and the second component, apply a transformation function to the similarity score computed based on applying the vector similarity function to the first component and the second component, and provide, as a boost factor, a numeric value for the personalization score based on a result of applying the transformation function to the similarity score, determine a revised ranking score for the particular topic in the list of popular topics using the personalization score and the popularity score for the particular topic, and rank the topics, in the list of popular topics, using the revised ranking score for the particular topic. | 10. A server device, of a topic ranking system, comprising: a memory to store: a user profile data structure that includes information about multiple users, and a topic data structure that includes topics, where each topic is assigned a popularity score; and a processor to execute instructions to: receive a request from a client device associated with a user, obtain, from the topic data structure, a list of popular topics for a particular time period, a ranking score for each topic in the list of popular topics, and a topic profile for a particular topic in the list of popular topics, identify a user profile for the user, determine a personalization score for the particular topic in the list of popular topics, where the personalization score for the particular topic is based on one or more similarities between the user profile and the topic profile for the particular topic, the processor, when determining the personalization score, being further to: represent the user profile as a first component that represents the user's interest in different subject matter categories, represent the topic profile as a second component that represents a relevance of the particular topic to the different subject matter categories, apply a vector similarity function to the first component and the second component to compute a similarity score for the first component and the second component, apply a transformation function to the similarity score computed based on applying the vector similarity function to the first component and the second component, and provide, as a boost factor, a numeric value for the personalization score based on a result of applying the transformation function to the similarity score, determine a revised ranking score for the particular topic in the list of popular topics using the personalization score and the popularity score for the particular topic, and rank the topics, in the list of popular topics, using the revised ranking score for the particular topic. 11. The server device of claim 10 , where the user profile includes one or more of: a personal identifier for the user, information regarding a language associated with the user, information regarding a geographic location associated with the user, or information regarding an interest associated with the user. | 0.685223 |
8,538,973 | 18 | 23 | 18. A system for ranking location search results of search queries, comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: receive a search query and a current location of a user; identify two or more places that satisfy the search query, and for each respective place determining a corresponding distance from the current location of the user to the respective place and a count of the number of historical queries for directions to the respective place, the respective place having a respective location; rank the two or more places in accordance with scores for each place, wherein the score for a respective place is based on the count of the number of historical directions queries for directions to the respective place, distances between the respective location of the respective place and origins in historical queries for directions to the respective location of the respective place, and the distance from the current location of the user to the respective place, to produce a set of ranked places; and provide the ranked set of places to the user. | 18. A system for ranking location search results of search queries, comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: receive a search query and a current location of a user; identify two or more places that satisfy the search query, and for each respective place determining a corresponding distance from the current location of the user to the respective place and a count of the number of historical queries for directions to the respective place, the respective place having a respective location; rank the two or more places in accordance with scores for each place, wherein the score for a respective place is based on the count of the number of historical directions queries for directions to the respective place, distances between the respective location of the respective place and origins in historical queries for directions to the respective location of the respective place, and the distance from the current location of the user to the respective place, to produce a set of ranked places; and provide the ranked set of places to the user. 23. The system of claim 18 , wherein the score for each respective place is based, at least in part, on a count obtained from historical records of search queries received from mobile devices in which a user-selected search result was the respective place. | 0.825137 |
8,494,847 | 1 | 3 | 1. A weighting factor learning system comprising: an audio recognition section that recognizes learning audio data and outputs a recognition result; a weighting factor updating section that updates a first weighting factor applied to an acoustic score obtained from an acoustic model and a second weighting factor applied to a language score obtained from a language model which are used in the audio recognition so that a difference between a correct-answer score calculated with the use of a correct-answer text of the learning audio data and a recognition-result score output from the audio recognition section becomes large; a convergence determination section that determines, with the use of the acoustic score after updating the first weighting factor and the language score after updating the second weighting factor, whether to return to the weighting factor updating section to update the first weighting factor and the second weighting factor again; and a weighting factor convergence determination section that determines, with the use of the acoustic score after updating the first weighting factor and the language score after updating the second weighting factor, whether to return to the audio recognition section to recognize the learning audio data and to output the recognition result using the audio recognition section, update the first weighting factor and the second weighting factor using the weighting factor updating section, and determine whether to return to the weighting factor updating section using the convergence determination section to update the first weighting factor and the second weighting factor again. | 1. A weighting factor learning system comprising: an audio recognition section that recognizes learning audio data and outputs a recognition result; a weighting factor updating section that updates a first weighting factor applied to an acoustic score obtained from an acoustic model and a second weighting factor applied to a language score obtained from a language model which are used in the audio recognition so that a difference between a correct-answer score calculated with the use of a correct-answer text of the learning audio data and a recognition-result score output from the audio recognition section becomes large; a convergence determination section that determines, with the use of the acoustic score after updating the first weighting factor and the language score after updating the second weighting factor, whether to return to the weighting factor updating section to update the first weighting factor and the second weighting factor again; and a weighting factor convergence determination section that determines, with the use of the acoustic score after updating the first weighting factor and the language score after updating the second weighting factor, whether to return to the audio recognition section to recognize the learning audio data and to output the recognition result using the audio recognition section, update the first weighting factor and the second weighting factor using the weighting factor updating section, and determine whether to return to the weighting factor updating section using the convergence determination section to update the first weighting factor and the second weighting factor again. 3. The weighting factor learning system according to claim 1 , wherein as the recognition result word sequences are selected and used among recognition candidate word sequences in descending order of a sum of the acoustic score and the language score, a number of the selected word sequences is determined in advance. | 0.815268 |
8,930,178 | 1 | 4 | 1. One or more non-transitory electronic memory devices including computer instructions for performing a method for processing natural language, the computer instructions being configured to perform the steps of: providing access to a clinical text, the clinical text including a plurality of groups of characters; providing access to a first database and a second database, the first database including associations between a plurality of known words and a plurality of semantic concepts, and the second database including associations between a plurality of episodic concepts and at least one of the plurality of known words and the plurality of semantic concepts, the plurality of episodic concepts being separate from the plurality of semantic concepts; identifying one or more of the plurality of groups of characters as corresponding to at least one of the plurality of known words; creating a list of the identified known words; querying the first database to obtain a set of one or more semantic concepts associated with each of the identified known words; annotating the list of identified known words with the set of semantic concepts associated with each identified known word; querying the second database to obtain a set of one or more episodic concepts associated with the set of semantic concepts; creating a semantic network having a plurality of nodes corresponding to the sets of semantic and episodic concepts and weighted links between the sets of semantic and episodic concepts; utilizing spreading activation algorithms to refine the weighted links in the semantic network; and selecting at least one of the concepts from the sets of semantic and episodic concepts based upon an associated weight for the at least one node derived from the step of utilizing spreading activation. | 1. One or more non-transitory electronic memory devices including computer instructions for performing a method for processing natural language, the computer instructions being configured to perform the steps of: providing access to a clinical text, the clinical text including a plurality of groups of characters; providing access to a first database and a second database, the first database including associations between a plurality of known words and a plurality of semantic concepts, and the second database including associations between a plurality of episodic concepts and at least one of the plurality of known words and the plurality of semantic concepts, the plurality of episodic concepts being separate from the plurality of semantic concepts; identifying one or more of the plurality of groups of characters as corresponding to at least one of the plurality of known words; creating a list of the identified known words; querying the first database to obtain a set of one or more semantic concepts associated with each of the identified known words; annotating the list of identified known words with the set of semantic concepts associated with each identified known word; querying the second database to obtain a set of one or more episodic concepts associated with the set of semantic concepts; creating a semantic network having a plurality of nodes corresponding to the sets of semantic and episodic concepts and weighted links between the sets of semantic and episodic concepts; utilizing spreading activation algorithms to refine the weighted links in the semantic network; and selecting at least one of the concepts from the sets of semantic and episodic concepts based upon an associated weight for the at least one node derived from the step of utilizing spreading activation. 4. The one or more non-transitory memory devices of claim 1 , wherein the clinical text comprises clinical free text. | 0.83795 |
8,166,394 | 7 | 11 | 7. The method of claim 1 further comprising, in response to receiving the input to add tracking to the content being created, graphically indicating objects for which tracking is available. | 7. The method of claim 1 further comprising, in response to receiving the input to add tracking to the content being created, graphically indicating objects for which tracking is available. 11. The method of claim 7 further comprising further comprising determining that tracking is available for the objects for which tracking is available by inspecting object type information for each objects in the electronic content. | 0.896243 |
9,767,825 | 15 | 18 | 15. An apparatus comprising: a first subsystem, implemented at least partially in hardware, that receives, from a content server, input media data with an input normal playback speed, the input media data comprising a plurality of input media data portions each having the same input normal playback speed; a second subsystem, implemented at least partially in hardware, that determines one or more user identities identified based at least in part on biometric data collected from one or more users who correspond to the one or more user identities and to whom audio utterance derived from the input media data is to be played; a third subsystem, implemented at least partially in hardware, that determines a preferred rate of audio utterance based at least in part on the one or more user identities; a fourth subsystem, implemented at least partially in hardware, that receives, from the content server, a plurality of rates of audio utterance for the plurality of input media data portions; a fifth subsystem, implemented at least partially in hardware, that, based at least in part on the preferred rate of audio utterance and the plurality of rates of audio utterance, generates audio output media data comprising a plurality of output media data portions having at least two different output normal playback speeds but the same preferred rate of audio utterance. | 15. An apparatus comprising: a first subsystem, implemented at least partially in hardware, that receives, from a content server, input media data with an input normal playback speed, the input media data comprising a plurality of input media data portions each having the same input normal playback speed; a second subsystem, implemented at least partially in hardware, that determines one or more user identities identified based at least in part on biometric data collected from one or more users who correspond to the one or more user identities and to whom audio utterance derived from the input media data is to be played; a third subsystem, implemented at least partially in hardware, that determines a preferred rate of audio utterance based at least in part on the one or more user identities; a fourth subsystem, implemented at least partially in hardware, that receives, from the content server, a plurality of rates of audio utterance for the plurality of input media data portions; a fifth subsystem, implemented at least partially in hardware, that, based at least in part on the preferred rate of audio utterance and the plurality of rates of audio utterance, generates audio output media data comprising a plurality of output media data portions having at least two different output normal playback speeds but the same preferred rate of audio utterance. 18. The apparatus as recited in claim 15 , further comprising: dividing the input media data into the plurality of input media data portions. | 0.787009 |
9,640,173 | 9 | 10 | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving text having a first part of the text and a second part of the text, wherein the text is associated with one language; identifying a recipient of speech to be generated from the text; identifying a location of the recipient of the speech; when the location comprises a first location: selecting a first language for the first part of the text and a second language for the second part of the text; generating first speech from the text, wherein the first speech comprises a first portion corresponding to the first part of the text and a second portion corresponding to the second part of the text, the first portion in the first language and the second portion in the second language; and communicating the first speech to the recipient; and when the location comprises a second location that differs from the first location: generating second speech from the text wherein the second speech comprises the first portion and the second portion both being in a same language; and communicating the second speech to the recipient. | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving text having a first part of the text and a second part of the text, wherein the text is associated with one language; identifying a recipient of speech to be generated from the text; identifying a location of the recipient of the speech; when the location comprises a first location: selecting a first language for the first part of the text and a second language for the second part of the text; generating first speech from the text, wherein the first speech comprises a first portion corresponding to the first part of the text and a second portion corresponding to the second part of the text, the first portion in the first language and the second portion in the second language; and communicating the first speech to the recipient; and when the location comprises a second location that differs from the first location: generating second speech from the text wherein the second speech comprises the first portion and the second portion both being in a same language; and communicating the second speech to the recipient. 10. The system of claim 9 , wherein the first language is a primary language of the recipient, and the second language is selected based on an original pronunciation of the second part of the text. | 0.66835 |
8,305,632 | 1 | 2 | 1. A method of processing a plurality of sheets of writing at a multifunction printer, the method comprising: scanning all of said sheets of writing; finding a cover sheet for a document in said scanned sheets of writing, said cover sheet having one or more of: an operation to be performed on said document; and additional processing instructions including instructions for performing one or more of: collating said document, stapling said document, and two-side printing said document; searching said scanned sheets of writing for flagging indicia, wherein said flagging indicia is one or more of a copyright notice or a security legend; in response to determining the presence of flagging indicia in one or more scanned sheets of said scanned sheets of writing, said multifunction printer: flagging one or more scanned sheets having flagging indicia from said one or more scanned sheets of writing; blocking processing of only said flagged one or more sheets from said one or more scanned sheets of writing, wherein access to said flagged one or more sheets is secured with an authorization code; identifying an individual that requested the processing of said document; storing an identity of said individual that requested the processing of said flagged one or more sheets in association with said flagged one or more sheets; transmitting only said flagged one or more sheets to an electronic mail address of a reviewer via an electronic mail; and in response to detecting said entry of said authorization code, removing said blocking of said flagged one or more sheets; and in response to said cover sheet having additional processing instructions, said multifunction printer performing said additional processing instructions on said document. | 1. A method of processing a plurality of sheets of writing at a multifunction printer, the method comprising: scanning all of said sheets of writing; finding a cover sheet for a document in said scanned sheets of writing, said cover sheet having one or more of: an operation to be performed on said document; and additional processing instructions including instructions for performing one or more of: collating said document, stapling said document, and two-side printing said document; searching said scanned sheets of writing for flagging indicia, wherein said flagging indicia is one or more of a copyright notice or a security legend; in response to determining the presence of flagging indicia in one or more scanned sheets of said scanned sheets of writing, said multifunction printer: flagging one or more scanned sheets having flagging indicia from said one or more scanned sheets of writing; blocking processing of only said flagged one or more sheets from said one or more scanned sheets of writing, wherein access to said flagged one or more sheets is secured with an authorization code; identifying an individual that requested the processing of said document; storing an identity of said individual that requested the processing of said flagged one or more sheets in association with said flagged one or more sheets; transmitting only said flagged one or more sheets to an electronic mail address of a reviewer via an electronic mail; and in response to detecting said entry of said authorization code, removing said blocking of said flagged one or more sheets; and in response to said cover sheet having additional processing instructions, said multifunction printer performing said additional processing instructions on said document. 2. The method as claimed in claim 1 , wherein finding said cover sheet comprises: performing optical character recognition on a first scanned sheet of writing; and searching said first scanned sheet of writing for cover sheet indicia. | 0.716019 |
10,120,933 | 1 | 6 | 1. A method of language processing that represents both sematic and orientation content within a text, the method being performed by circuitry included in a computing device, the method comprising: receiving, by the circuitry, ordered data elements representing respective words in a text, the ordered data elements including a first data element including one or more words and a second data element, which is sequential with the first data element and include another one or more words; generating, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encoding by the circuitry, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; computing by the circuitry, respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution being computed using respective ordered pairs for each of the one or more first semantic classes with respect to each of the one or more second semantic classes; and determining a dominant semantic class of an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of an ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. | 1. A method of language processing that represents both sematic and orientation content within a text, the method being performed by circuitry included in a computing device, the method comprising: receiving, by the circuitry, ordered data elements representing respective words in a text, the ordered data elements including a first data element including one or more words and a second data element, which is sequential with the first data element and include another one or more words; generating, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encoding by the circuitry, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; computing by the circuitry, respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution being computed using respective ordered pairs for each of the one or more first semantic classes with respect to each of the one or more second semantic classes; and determining a dominant semantic class of an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of an ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. 6. The method of claim 1 , wherein the encoding of the first data element with respect to the second data element is performed for each semantic class of the one or more first semantic classes relative to each semantic class of the one or more second semantic classes, and each semantic class of the one or more second semantic classes is different than each semantic class of the one or more first semantic classes. | 0.534676 |
6,108,004 | 19 | 22 | 19. A computer-based system used to develop executable data mining profiles comprising: a main menu interface listing one or more data mining object types and associated sub-objects, said data mining object types comprising one or more from the group of: data, discretization, mining, name mapping, processing, results, sequence, statistics and taxonomy; a series of context sensitive GUI templates, the selection of subsequent context sensitive templates based on one or more inputs to one or more proceeding GUI templates, said GUI templates requesting data object mining parameters for one of said data mining object types; said data mining sub-objects created by traversal of said series of GUI templates based on data object mining parameters of a previous GUI template; and an executable data mining profile created by a selective grouping of created mining sub-objects, said executable data mining profile comprising sequences of settings that run consecutively, said settings including one or more of processing, mining, sequence or statistics. | 19. A computer-based system used to develop executable data mining profiles comprising: a main menu interface listing one or more data mining object types and associated sub-objects, said data mining object types comprising one or more from the group of: data, discretization, mining, name mapping, processing, results, sequence, statistics and taxonomy; a series of context sensitive GUI templates, the selection of subsequent context sensitive templates based on one or more inputs to one or more proceeding GUI templates, said GUI templates requesting data object mining parameters for one of said data mining object types; said data mining sub-objects created by traversal of said series of GUI templates based on data object mining parameters of a previous GUI template; and an executable data mining profile created by a selective grouping of created mining sub-objects, said executable data mining profile comprising sequences of settings that run consecutively, said settings including one or more of processing, mining, sequence or statistics. 22. A computer-based system used to develop data mining objects as per claim 19, wherein said main menu comprises a plurality of windows, a first window displaying said listed data mining object types and additionally sub-objects, a second window displaying said sub-objects and a third window displaying a heterogenous selection of said sub-objects. | 0.616228 |
8,640,026 | 15 | 18 | 15. A word correction system, comprising: a multi-touch device comprising a user interface, wherein the multi-touch device is configured to receive touch input from a user to interact with the user interface; and a word correction engine, configured to: detect a selection by the user of a word displayed in the user interface; break the word into logical segments, wherein at least one of the logical segments comprises a plurality of characters; present the logical segments in the user interface; detect a user-selected segment of one of the logical segments; display at least one alternative segment for the user-selected segment in the user interface; and alter the selected segment in response to receiving a user-selected replacement from the at least one alternative segment. | 15. A word correction system, comprising: a multi-touch device comprising a user interface, wherein the multi-touch device is configured to receive touch input from a user to interact with the user interface; and a word correction engine, configured to: detect a selection by the user of a word displayed in the user interface; break the word into logical segments, wherein at least one of the logical segments comprises a plurality of characters; present the logical segments in the user interface; detect a user-selected segment of one of the logical segments; display at least one alternative segment for the user-selected segment in the user interface; and alter the selected segment in response to receiving a user-selected replacement from the at least one alternative segment. 18. The system of claim 15 , wherein breaking the word into logical segments further comprises separating the word into syllables. | 0.894481 |
9,308,446 | 1 | 15 | 1. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games, wherein one of the social cue perception games challenges the participant to observe gaze directions in facial images; one or more computerized emotion perception games; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range. | 1. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games, wherein one of the social cue perception games challenges the participant to observe gaze directions in facial images; one or more computerized emotion perception games; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range. 15. The training program of claim 1 , further comprising one or more self-referential games, wherein one of the self-referential games challenges the participant to match pictures that have a common affect. | 0.576132 |
9,286,887 | 17 | 18 | 17. The computer-readable storage device of claim 16 , having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising analyzing a speech recognition error probability to determine an alternative character combination from the correlation table most likely to match the speech input. | 17. The computer-readable storage device of claim 16 , having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising analyzing a speech recognition error probability to determine an alternative character combination from the correlation table most likely to match the speech input. 18. The computer-readable storage device of claim 17 , wherein the speech recognition error probability comprises a likelihood that the speech input was incorrectly recognized by a speech recognizer. | 0.879101 |
8,051,459 | 32 | 35 | 32. A program product stored on a non-transitory computer useable medium for enforcement of Trusted Computing (TC) in a Security Enhanced Linux (SELinux) operating system, the program product comprising program code for causing a computer system to perform the following steps: upon receiving a request from a subject process for access to an object, obtaining values for TC-related attributes that specify TC-related policies, wherein the TC-related policies are maintained in an extended SELinux policy model; and enforcing the TC-related policies by making access control decisions based on the obtained values for the TC-related attributes. | 32. A program product stored on a non-transitory computer useable medium for enforcement of Trusted Computing (TC) in a Security Enhanced Linux (SELinux) operating system, the program product comprising program code for causing a computer system to perform the following steps: upon receiving a request from a subject process for access to an object, obtaining values for TC-related attributes that specify TC-related policies, wherein the TC-related policies are maintained in an extended SELinux policy model; and enforcing the TC-related policies by making access control decisions based on the obtained values for the TC-related attributes. 35. The program product of claim 32 further including program code for making access control decisions based on the obtained values for the TC-related attributes in addition to SELinux Type Enforcement. | 0.502463 |
9,401,099 | 8 | 9 | 8. The method of claim 1 , wherein the context indicates a window type associated with the at least some of the text. | 8. The method of claim 1 , wherein the context indicates a window type associated with the at least some of the text. 9. The method of claim 8 , wherein a same word or phrase in the closed-captioning content is replaced with different symbols in different window types. | 0.977943 |
8,700,414 | 7 | 8 | 7. The method of claim 5 , wherein events include events representing criteria met, transactions being created, conditions of business data being satisfied and events representing the lack of occurrence of an expected event. | 7. The method of claim 5 , wherein events include events representing criteria met, transactions being created, conditions of business data being satisfied and events representing the lack of occurrence of an expected event. 8. The method of claim 7 , wherein alerts include alerts according to alert rules that specify that particular participants are to be alerted when expected events do not occur when expected or as expected. | 0.961262 |
8,176,032 | 10 | 16 | 10. A system comprising: a query monitoring module to: monitor search queries associated with a search query category, the search query category associated with at least one search term and associated with a baseline frequency, the baseline frequency reflecting an average number of search queries detected during a time interval associated with the search query category, and detect a change in a search request frequency associated with the search query category with respect to the baseline frequency; an event detecting module to determine an event associated with the search query category; an item identifying module to identify one or more data items associated with the event, the one or more items comprising at least one item listing associated with an item for sale; and at least one processor to run a display generation module configured to generate a visual representation of a relationship between the one or more data items and the event, the display generation module configured to display the at least one item listing such that the at least one item listing appears visually related to the event. | 10. A system comprising: a query monitoring module to: monitor search queries associated with a search query category, the search query category associated with at least one search term and associated with a baseline frequency, the baseline frequency reflecting an average number of search queries detected during a time interval associated with the search query category, and detect a change in a search request frequency associated with the search query category with respect to the baseline frequency; an event detecting module to determine an event associated with the search query category; an item identifying module to identify one or more data items associated with the event, the one or more items comprising at least one item listing associated with an item for sale; and at least one processor to run a display generation module configured to generate a visual representation of a relationship between the one or more data items and the event, the display generation module configured to display the at least one item listing such that the at least one item listing appears visually related to the event. 16. The system of claim 10 , wherein the item identifying module is to: query an item database with one or more search terms from the search query category; receive an identification of the one or more data items. | 0.754608 |
9,537,674 | 1 | 10 | 1. A method for notifying a user of a computer having a display about incoming messages stored in an inbox, the method comprising: a) receiving size information and originator information about a plurality of messages in the inbox; b) for each of the plurality of messages, generating a message visualization structure associated with the respective message, and determining a first non-textual visual feature of the message visualization structure on the basis of the size information of the message and a second non-textual visual feature of the message visualization structure on the basis of the originator information of the respective message; c) rendering on the display the visualization structures within a graphical environment in which the message visualization structures convey information about the messages, their respective size information, and their respective originator information in a non-textual-list manner, wherein at least one of the first non-textual visual feature and the second non-textual visual feature includes an animation of the message visualization structure associated with the corresponding message. | 1. A method for notifying a user of a computer having a display about incoming messages stored in an inbox, the method comprising: a) receiving size information and originator information about a plurality of messages in the inbox; b) for each of the plurality of messages, generating a message visualization structure associated with the respective message, and determining a first non-textual visual feature of the message visualization structure on the basis of the size information of the message and a second non-textual visual feature of the message visualization structure on the basis of the originator information of the respective message; c) rendering on the display the visualization structures within a graphical environment in which the message visualization structures convey information about the messages, their respective size information, and their respective originator information in a non-textual-list manner, wherein at least one of the first non-textual visual feature and the second non-textual visual feature includes an animation of the message visualization structure associated with the corresponding message. 10. A method as defined in claim 1 , including communicating with a message service that includes the inbox to gather the size information. | 0.889507 |
7,797,293 | 39 | 40 | 39. The device of claim 23 , wherein each contact entry comprises historical context information indicating context information associated with the contact entry's past usage, wherein in said identifying the program instructions are configured to identify one or more context appropriate contact entries from the entries according to each entry's historical context information. | 39. The device of claim 23 , wherein each contact entry comprises historical context information indicating context information associated with the contact entry's past usage, wherein in said identifying the program instructions are configured to identify one or more context appropriate contact entries from the entries according to each entry's historical context information. 40. The device of claim 39 , wherein the program instructions are further configured to update the historical context information for each of the context appropriate contact entries based on the current context information. | 0.939138 |
9,305,051 | 1 | 5 | 1. A computer-implemented method, comprising: extracting query reformulations from search logs, each of the query reformulations including an initial query and a query qualifier not specified in the initial query; clustering the extracted query reformulations into clusters using modified star clustering such that a set of query aspects is identified, the set of query aspects including query qualifiers of the query reformulations, wherein clustering includes generating star-shaped subgraphs using the query qualifiers, wherein clustering is performed without using the query reformulations or corresponding queries; receiving a search query; identifying query aspects for the search query from the set of query aspects such that a similarity measure is maximized; and presenting the identified query aspects along with results of the search query, wherein the identified query aspects are presented as options for refinement of the search query. | 1. A computer-implemented method, comprising: extracting query reformulations from search logs, each of the query reformulations including an initial query and a query qualifier not specified in the initial query; clustering the extracted query reformulations into clusters using modified star clustering such that a set of query aspects is identified, the set of query aspects including query qualifiers of the query reformulations, wherein clustering includes generating star-shaped subgraphs using the query qualifiers, wherein clustering is performed without using the query reformulations or corresponding queries; receiving a search query; identifying query aspects for the search query from the set of query aspects such that a similarity measure is maximized; and presenting the identified query aspects along with results of the search query, wherein the identified query aspects are presented as options for refinement of the search query. 5. The method of claim 1 , wherein the search query includes a search term and one or more qualifiers, wherein identifying query aspects for the search query from the set of query aspects is performed such that a similarity measure based, at least in part, upon the qualifiers and the identified query aspects, is maximized. | 0.55 |
9,734,181 | 21 | 25 | 21. A system, the system comprising: one or more processors; system memory coupled to the one or more hardware processors, the system memory storing instructions that are executable by the one or more hardware processors; and the one or more hardware processors executing the instructions stored in the system memory to detect one or more subject columns of a table, including the following: select a specified number of columns from the table as candidate subject columns, each candidate subject column being a candidate for a true subject column of the table, each candidate subject column including a plurality of values; for each subject candidate column: determine a co-occurrence for values in the candidate subject column, including determining how often values in the candidate subject column also occur in true subject columns in a plurality of other tables; and calculate a score for the candidate subject column based on the determined co-occurrence, the calculated score indicating a likelihood of the candidate subject column being a true subject column; and classify the candidate subject column as one of: a true subject column of the table or a non-subject column of the table based on the calculated score for the candidate subject column. | 21. A system, the system comprising: one or more processors; system memory coupled to the one or more hardware processors, the system memory storing instructions that are executable by the one or more hardware processors; and the one or more hardware processors executing the instructions stored in the system memory to detect one or more subject columns of a table, including the following: select a specified number of columns from the table as candidate subject columns, each candidate subject column being a candidate for a true subject column of the table, each candidate subject column including a plurality of values; for each subject candidate column: determine a co-occurrence for values in the candidate subject column, including determining how often values in the candidate subject column also occur in true subject columns in a plurality of other tables; and calculate a score for the candidate subject column based on the determined co-occurrence, the calculated score indicating a likelihood of the candidate subject column being a true subject column; and classify the candidate subject column as one of: a true subject column of the table or a non-subject column of the table based on the calculated score for the candidate subject column. 25. The system of claim 21 , wherein the one or more hardware processors executing the instructions stored in the system memory to calculate a score for the candidate subject column comprises the one or more hardware processors executing the instructions stored in the system memory to calculate a score for the candidate subject column based on the occurrence of the values in a knowledge base. | 0.664686 |
10,002,165 | 1 | 5 | 1. A system, comprising: a processor; and a memory storing a program, which, when executed on the processor, performs an operation for ranking search results received from a plurality of distinct search resources, the operation comprising: receiving a search query over a communications network from a software application executing on a client device; transmitting the search query to a plurality of search resources via the communications network; receiving, from each of the plurality of search resources, a set of ranked search results, wherein each search result identifies an item and wherein each search result includes metadata characterizing the item and a link to a full version of the item; determining a unified match score for each search result in the received sets of ranked search results by summing matching scores of each search result ranked below the respective search result in the respective received set of ranked search results, wherein a unified match score of a first ranked search result is determined based on metadata of the first ranked search result and metadata of each second ranked search result having a lower rank than the first ranked search result in the associated set of ranked search results and wherein the metadata characterizing items identified in each ranked search result includes a title of the item and a summary of the item; determining a unified ranking for the ranked search results in the received sets of ranked search results based on the determined unified match scores for each search result, wherein the unified ranking maintains a relative ranking of each set of ranked search results as received from the plurality of search resources; ordering the search results by the determined unified ranking; generating a presentation of the ordered search results, wherein each respective search result included in the presentation comprises the link to the full version of the respective item identified by the respective search result; and sending the presentation of the ordered search results over the communications network to the software application executing on the client device. | 1. A system, comprising: a processor; and a memory storing a program, which, when executed on the processor, performs an operation for ranking search results received from a plurality of distinct search resources, the operation comprising: receiving a search query over a communications network from a software application executing on a client device; transmitting the search query to a plurality of search resources via the communications network; receiving, from each of the plurality of search resources, a set of ranked search results, wherein each search result identifies an item and wherein each search result includes metadata characterizing the item and a link to a full version of the item; determining a unified match score for each search result in the received sets of ranked search results by summing matching scores of each search result ranked below the respective search result in the respective received set of ranked search results, wherein a unified match score of a first ranked search result is determined based on metadata of the first ranked search result and metadata of each second ranked search result having a lower rank than the first ranked search result in the associated set of ranked search results and wherein the metadata characterizing items identified in each ranked search result includes a title of the item and a summary of the item; determining a unified ranking for the ranked search results in the received sets of ranked search results based on the determined unified match scores for each search result, wherein the unified ranking maintains a relative ranking of each set of ranked search results as received from the plurality of search resources; ordering the search results by the determined unified ranking; generating a presentation of the ordered search results, wherein each respective search result included in the presentation comprises the link to the full version of the respective item identified by the respective search result; and sending the presentation of the ordered search results over the communications network to the software application executing on the client device. 5. The system of claim 1 , wherein at least one of the search resources is one of a web-based search engine, a public access library database, a government database, or a corporate database. | 0.637405 |
9,507,853 | 15 | 16 | 15. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining a first search results score associated with first search results obtained for a search query that was obtained by a user, wherein the first search results score is based on (i) a respective rank of each first search result, and (ii) a respective first popularity score associated with each first search result; revising the search query using a query revision rule to determine a revised search query; determining a second search results score associated with second search results obtained for the revised search query, wherein the second search results score is based on (i) a respective rank of each second search result, and (ii) a respective second popularity score associated with each second search result; comparing the first search results score with the second search results score; based on the comparison of the first search results score with the second search results score, storing the query revision rule in a collection of rules that are used to revise future search queries; and using one or more rules in the stored collection of rules, which includes the query revision rule, to revise a new search query. | 15. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining a first search results score associated with first search results obtained for a search query that was obtained by a user, wherein the first search results score is based on (i) a respective rank of each first search result, and (ii) a respective first popularity score associated with each first search result; revising the search query using a query revision rule to determine a revised search query; determining a second search results score associated with second search results obtained for the revised search query, wherein the second search results score is based on (i) a respective rank of each second search result, and (ii) a respective second popularity score associated with each second search result; comparing the first search results score with the second search results score; based on the comparison of the first search results score with the second search results score, storing the query revision rule in a collection of rules that are used to revise future search queries; and using one or more rules in the stored collection of rules, which includes the query revision rule, to revise a new search query. 16. The system of claim 15 , wherein the operations further comprise: obtaining ranking information associated with the first search results; and obtaining first popularity scores associated with the first search results, wherein a first popularity score reflects the popularity of a search result in connection with the search query. | 0.569588 |
7,809,665 | 3 | 4 | 3. The computer implemented method of claim 1 , further comprising: obtaining input data identifying a record; and classifying the record identified by the obtained input data using rule-based classification data of at least one of the identified rule-based classifiers. | 3. The computer implemented method of claim 1 , further comprising: obtaining input data identifying a record; and classifying the record identified by the obtained input data using rule-based classification data of at least one of the identified rule-based classifiers. 4. The computer implemented method of claim 3 , wherein classifying the record comprises classifying the record according to a hard classification method or a soft classification method. | 0.954345 |
9,015,143 | 22 | 26 | 22. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; obtaining a respective snippet for each of first multiple search results, wherein the first multiple search results are selected from among the set of search results; providing, for display, a search engine results page that includes (i) the first multiple search results from among the set of search results that the search engine identifies as responsive to the search query, (ii) the respective snippet for each of the first multiple search results, and (iii) a text entry field for entering a refinement to the search query; receiving data indicating the refinement to the search query that is entered through the text entry field on the search engine results page; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results, wherein each search result of the subset of search results references a respective resource that satisfies the refinement, and wherein the subset of search results are obtained without instructing the search engine to perform a subsequent search; obtaining a respective updated snippet for each of second multiple search results, wherein the second multiple search results are selected from among the subset of search results; and providing, for display, an updated search engine results page that includes (i) the second multiple search results that are selected from among the subset of the search results, and (ii) the respective updated snippet for each of the second multiple search results. | 22. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; obtaining a respective snippet for each of first multiple search results, wherein the first multiple search results are selected from among the set of search results; providing, for display, a search engine results page that includes (i) the first multiple search results from among the set of search results that the search engine identifies as responsive to the search query, (ii) the respective snippet for each of the first multiple search results, and (iii) a text entry field for entering a refinement to the search query; receiving data indicating the refinement to the search query that is entered through the text entry field on the search engine results page; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results, wherein each search result of the subset of search results references a respective resource that satisfies the refinement, and wherein the subset of search results are obtained without instructing the search engine to perform a subsequent search; obtaining a respective updated snippet for each of second multiple search results, wherein the second multiple search results are selected from among the subset of search results; and providing, for display, an updated search engine results page that includes (i) the second multiple search results that are selected from among the subset of the search results, and (ii) the respective updated snippet for each of the second multiple search results. 26. The system of claim 22 , wherein providing, for display, the updated search engine results page comprises replacing a snippet included with a particular search result presented on the search engine results page with the respective updated snippet for the particular search result. | 0.538961 |
7,536,713 | 1 | 7 | 1. A method for classifying and retrieving information comprising: reviewing a document by a content producer device; determining a category attribute value, a context attribute value, and a keyword attribute value of said document wherein said category attribute value, said context attribute value, and said keyword attribute value describe said document, wherein said category attribute value comprises a general classification category, said context attribute value comprises a classification type, and said keyword attribute value comprises a classification detail; generating a knowledge attribute data using a computer programmed to reduce said category attribute value, said context attribute value, and said keyword attribute value to a single data value, wherein said knowledge attribute data is represented as a pseudo-unique numeric value generated using a hash function; creating a knowledge object comprising an attribute specification that contains a document representation of said document and said knowledge attribute data, wherein allowing selective distribution based on subscriber-based forwarding, where a client device requests to have only knowledge objects matching said document to be forwarded; storing said knowledge object in a search engine database on a server; receiving a search query comprising a category search parameter, a context search parameter, and a keyword search parameter from a content consumer device wherein said category search parameter comprises a general classification category search parameter, said context search parameter comprises a classification type search parameter, and said keyword search parameter comprises a classification detail search parameter; generating a search attribute data by reducing said search query comprising said category search parameter, said context search parameter, and said keyword search parameter to a single data value, wherein said search attribute data is represented as a pseudo-unique numeric value generated using a hash function; retrieving said knowledge attribute data from said search engine database; comparing said search attribute data with said knowledge attribute data; and, when said comparing results in a match, presenting said knowledge object to said content consumer device. | 1. A method for classifying and retrieving information comprising: reviewing a document by a content producer device; determining a category attribute value, a context attribute value, and a keyword attribute value of said document wherein said category attribute value, said context attribute value, and said keyword attribute value describe said document, wherein said category attribute value comprises a general classification category, said context attribute value comprises a classification type, and said keyword attribute value comprises a classification detail; generating a knowledge attribute data using a computer programmed to reduce said category attribute value, said context attribute value, and said keyword attribute value to a single data value, wherein said knowledge attribute data is represented as a pseudo-unique numeric value generated using a hash function; creating a knowledge object comprising an attribute specification that contains a document representation of said document and said knowledge attribute data, wherein allowing selective distribution based on subscriber-based forwarding, where a client device requests to have only knowledge objects matching said document to be forwarded; storing said knowledge object in a search engine database on a server; receiving a search query comprising a category search parameter, a context search parameter, and a keyword search parameter from a content consumer device wherein said category search parameter comprises a general classification category search parameter, said context search parameter comprises a classification type search parameter, and said keyword search parameter comprises a classification detail search parameter; generating a search attribute data by reducing said search query comprising said category search parameter, said context search parameter, and said keyword search parameter to a single data value, wherein said search attribute data is represented as a pseudo-unique numeric value generated using a hash function; retrieving said knowledge attribute data from said search engine database; comparing said search attribute data with said knowledge attribute data; and, when said comparing results in a match, presenting said knowledge object to said content consumer device. 7. The method of claim 1 , wherein said document representation comprises a pointer to said document. | 0.864973 |
6,137,041 | 1 | 4 | 1. A music score reading method comprising: recognizing all signs and notes of a music score, in a sian recognizing step; estimating a drum notation in a drum part of the music score based on information obtained by said recognizing step, in a notation estimating step; and allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating step, in a musical instrument allocating step, such that the music score is converted into a readable music score data format. | 1. A music score reading method comprising: recognizing all signs and notes of a music score, in a sian recognizing step; estimating a drum notation in a drum part of the music score based on information obtained by said recognizing step, in a notation estimating step; and allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating step, in a musical instrument allocating step, such that the music score is converted into a readable music score data format. 4. A music score reading method according to claim 1 wherein said notation estimating step estimates a drum notation with respect to drum instruments other than cymbals such that, if heads exist in a third space of the staff and a black head and a head of another kind are detected, the black head is set to a snare drum while (R) or the head other than the black head is set to a rim shot and, if heads exist in the third space of the staff and only the black heads are detected and further a character string representing the rim shot is detected, the black head designated by said character string is set to the rim shot while the other black head is set to the snare drum. | 0.801293 |
7,877,258 | 1 | 2 | 1. A computer-implemented method comprising: generating a compact language model, including: receiving a collection of n-grams from a corpus, each n-gram of the collection having a corresponding first probability of occurring in the corpus, and generating a trie representing the collection of n-grams including calculating a left word vector and a diversity count vector using the collection of n grams, the left word vector identifying each distinct left word for a given right context in the collection, the diversity count vector identifying a count of distinct left words for each right context in the collection, and using the language model to identify a second probability of a particular string of words occurring; and wherein generating, receiving and using are performed by one or more data processing apparatuses. | 1. A computer-implemented method comprising: generating a compact language model, including: receiving a collection of n-grams from a corpus, each n-gram of the collection having a corresponding first probability of occurring in the corpus, and generating a trie representing the collection of n-grams including calculating a left word vector and a diversity count vector using the collection of n grams, the left word vector identifying each distinct left word for a given right context in the collection, the diversity count vector identifying a count of distinct left words for each right context in the collection, and using the language model to identify a second probability of a particular string of words occurring; and wherein generating, receiving and using are performed by one or more data processing apparatuses. 2. The method of claim 1 , further comprising: representing entries in the left word vector and diversity count vector as integers; and encoding the left word vector and the diversity count vector using block encoding, where the block encoding encodes blocks of integers in each respective vector. | 0.713873 |
8,141,011 | 7 | 15 | 7. One or more non-transitory computer readable media storing instructions executable by a processor, the media storing one or more instructions for: generating an intermediate representation of a state diagram, the intermediate representation being generated based on syntax and semantics of the state diagram, the intermediate representation representing semantics of the state diagram; mapping the semantics represented by the intermediate representation to semantics of a hardware description language; and generating code in the hardware description language based on the mapping of the semantics represented by the intermediate representation to semantics of the hardware description language. | 7. One or more non-transitory computer readable media storing instructions executable by a processor, the media storing one or more instructions for: generating an intermediate representation of a state diagram, the intermediate representation being generated based on syntax and semantics of the state diagram, the intermediate representation representing semantics of the state diagram; mapping the semantics represented by the intermediate representation to semantics of a hardware description language; and generating code in the hardware description language based on the mapping of the semantics represented by the intermediate representation to semantics of the hardware description language. 15. The media of claim 7 , further storing one or more instructions for: adding one or more standard interface signals to the generated code. | 0.886107 |
7,921,184 | 1 | 8 | 1. In a network device, a method for responding to a request for a dynamically generated object from a plurality of clients, the method comprising the steps of: receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; transmitting, by the cache manager, the first request to the originating server; receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and flushing, by the cache manager, the dynamically generated object from the transmission buffer, responsive to completion of transmission of the dynamically generated object to the first client and the second client. | 1. In a network device, a method for responding to a request for a dynamically generated object from a plurality of clients, the method comprising the steps of: receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; transmitting, by the cache manager, the first request to the originating server; receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and flushing, by the cache manager, the dynamically generated object from the transmission buffer, responsive to completion of transmission of the dynamically generated object to the first client and the second client. 8. The method of claim 1 , comprising modifying the response to include one of an entity tag header or a cache-control header and transmitting the modified response to one of the first client or the second client. | 0.784848 |
9,142,213 | 7 | 12 | 7. A computer program product comprising: a plurality of computer-executable instructions recorded on a non-transitory computer-readable media, wherein said computer-executable instructions, when executed by at least one computer system, cause the at least one computer system to: receive in the at least one computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyze the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model. | 7. A computer program product comprising: a plurality of computer-executable instructions recorded on a non-transitory computer-readable media, wherein said computer-executable instructions, when executed by at least one computer system, cause the at least one computer system to: receive in the at least one computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyze the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model. 12. The computer program product of claim 7 , wherein the dialog-oriented language is VoiceXML language for which the dialog unit code is a VoiceXML Form and the code for direct attribute value acquisition in the form is a VoiceXML Field. | 0.847826 |
7,603,626 | 22 | 25 | 22. In a computer network comprising a host computer system and a plurality of computers associated with a plurality of participants having access to the host system over the network, a method of creating a collaborative work, the collaborative work including multiple segments submitted by multiple participants, the method comprising: presenting to the multiple participants instructions for creating a segment; receiving from at least a subset of the multiple participants segments submitted over the network; presenting the submitted segments to a voting audience over the network to vote for a favored segment; and creating the collaborative work by selecting winning segments based on the votes submitted by the voting audience, wherein a promo, which is only authored by the author of the submitted segment and constitutes a subset of the submitted segment, is submitted with each submitted segment candidate, said promo being indicative of the content of the submitted segment candidate, wherein said promo is designed to generate interest amongst members of the voting audience to view the submitted segment in full, wherein said promo comprises an image or graphic, and a title, summary and excerpt, and wherein participation in said voting audience is open to the general public. | 22. In a computer network comprising a host computer system and a plurality of computers associated with a plurality of participants having access to the host system over the network, a method of creating a collaborative work, the collaborative work including multiple segments submitted by multiple participants, the method comprising: presenting to the multiple participants instructions for creating a segment; receiving from at least a subset of the multiple participants segments submitted over the network; presenting the submitted segments to a voting audience over the network to vote for a favored segment; and creating the collaborative work by selecting winning segments based on the votes submitted by the voting audience, wherein a promo, which is only authored by the author of the submitted segment and constitutes a subset of the submitted segment, is submitted with each submitted segment candidate, said promo being indicative of the content of the submitted segment candidate, wherein said promo is designed to generate interest amongst members of the voting audience to view the submitted segment in full, wherein said promo comprises an image or graphic, and a title, summary and excerpt, and wherein participation in said voting audience is open to the general public. 25. The method according to claim 22 , wherein the segment instructions for the collaborative work are provided to the multiple participants for all of the segments that comprise the collaborative work at the same time. | 0.89006 |
9,992,534 | 5 | 6 | 5. The method of claim 1 , wherein the channel switching interface is automatically displayed in a mobile application on the first display device when the user comes within proximity to the second display device. | 5. The method of claim 1 , wherein the channel switching interface is automatically displayed in a mobile application on the first display device when the user comes within proximity to the second display device. 6. The method of claim 5 , wherein the mobile application is displayed in place of a lock screen on the first display device. | 0.94856 |
8,812,969 | 34 | 36 | 34. A non-transitory computer readable storage medium with instructions thereon which, when executed by a system, cause the system to perform a method comprising: extracting a plurality of visual, audible, and audiovisual document elements from content contained within an input document, wherein the input document comprises a single file; automatically selecting two or more visual, audible, or audiovisual document elements from the extracted visual, audible, and audiovisual document elements of the input document for inclusion into a multimedia representation of the input document based on one or more optimizing constraints to maximize a total of information content provided by the selected two or more visual, audible, or audiovisual document elements in a given amount of time, wherein the one or more optimizing constraints comprise one or more characteristics of a device displaying a graphical user interface and one or more application constraints, wherein the automatic selection comprises calculating a time attribute and an information attribute for each of the extracted visual, audible, and audiovisual document elements and selecting one or more visual, audible, or audiovisual document elements based on each time attribute and each information attribute, wherein each time attribute is calculated, using the one or more characteristics of the device that is to display the multimedia representation, to determine a minimum presentation time for a user to comprehend each of the extracted visual, audible, and audiovisual document elements, and wherein each information attribute is calculated, using the one or more application constraints, to determine an amount of information content that is contained in each of the extracted visual, audible, and audiovisual document elements, and wherein automatically selecting two or more of the extracted visual, audible, or audiovisual document elements to maximize the total of information content provided by the selected visual, audible, or audiovisual document elements in the given amount of time, further comprises: selecting audible document elements that maximize an amount of information contained in the selected audible document elements when presented in one or more time intervals of an audible channel of the multimedia representation that have not been filled with audio data associated with the selected audiovisual elements, and filling the one or more time intervals of the audible channel with the selected audible document elements; automatically generating the multimedia representation based on the automatically selected one or more visual, audible, or audiovisual document elements; providing an interactive user interface to playback a combination of the multimedia representation and the input document under user control. | 34. A non-transitory computer readable storage medium with instructions thereon which, when executed by a system, cause the system to perform a method comprising: extracting a plurality of visual, audible, and audiovisual document elements from content contained within an input document, wherein the input document comprises a single file; automatically selecting two or more visual, audible, or audiovisual document elements from the extracted visual, audible, and audiovisual document elements of the input document for inclusion into a multimedia representation of the input document based on one or more optimizing constraints to maximize a total of information content provided by the selected two or more visual, audible, or audiovisual document elements in a given amount of time, wherein the one or more optimizing constraints comprise one or more characteristics of a device displaying a graphical user interface and one or more application constraints, wherein the automatic selection comprises calculating a time attribute and an information attribute for each of the extracted visual, audible, and audiovisual document elements and selecting one or more visual, audible, or audiovisual document elements based on each time attribute and each information attribute, wherein each time attribute is calculated, using the one or more characteristics of the device that is to display the multimedia representation, to determine a minimum presentation time for a user to comprehend each of the extracted visual, audible, and audiovisual document elements, and wherein each information attribute is calculated, using the one or more application constraints, to determine an amount of information content that is contained in each of the extracted visual, audible, and audiovisual document elements, and wherein automatically selecting two or more of the extracted visual, audible, or audiovisual document elements to maximize the total of information content provided by the selected visual, audible, or audiovisual document elements in the given amount of time, further comprises: selecting audible document elements that maximize an amount of information contained in the selected audible document elements when presented in one or more time intervals of an audible channel of the multimedia representation that have not been filled with audio data associated with the selected audiovisual elements, and filling the one or more time intervals of the audible channel with the selected audible document elements; automatically generating the multimedia representation based on the automatically selected one or more visual, audible, or audiovisual document elements; providing an interactive user interface to playback a combination of the multimedia representation and the input document under user control. 36. The non-transitory computer readable storage medium of claim 34 wherein providing an interactive user interface further comprises: playing back the multimedia representation of a portion of a document page when the portion of the document page is selected in a document viewing interface; and automatically resizing the selected portion of the page in the multimedia representation. | 0.8 |
8,538,976 | 13 | 14 | 13. A system, comprising: a processor; and a memory storing an application program, which, when executed on the processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields. | 13. A system, comprising: a processor; and a memory storing an application program, which, when executed on the processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields. 14. The system of claim 13 , wherein the operation further comprises: adding the generated second logical field to the plurality of logical fields; and providing a query interface to compose abstract queries. | 0.770419 |
9,373,321 | 1 | 3 | 1. A method for generating one or more wake-up words, the method comprising: receiving, using a keyboard, a text representation of the one or more wake-up words; determining a strength of the text representation of the one or more wake-up words based on one or more static measures, wherein the determining the strength of the text representation comprises applying a Kullback-Leibler (KL) divergence calculation between the one or more wake-up words and words unrelated to the one or more wake-up words; comparing a result of the KL divergence calculation to a predetermined distance score associated with a decoding accuracy of a speech recognizer; receiving, using a microphone, an audio representation of the one or more wake-up words; determining a strength of the audio representation of the one or more wake-up words based on one or more dynamic measures; and providing a message on a display device, wherein the message comprises one or more improvements to a likelihood that the speech recognizer recognizes the one or more wake-up words based on the strengths of the text and audio representations. | 1. A method for generating one or more wake-up words, the method comprising: receiving, using a keyboard, a text representation of the one or more wake-up words; determining a strength of the text representation of the one or more wake-up words based on one or more static measures, wherein the determining the strength of the text representation comprises applying a Kullback-Leibler (KL) divergence calculation between the one or more wake-up words and words unrelated to the one or more wake-up words; comparing a result of the KL divergence calculation to a predetermined distance score associated with a decoding accuracy of a speech recognizer; receiving, using a microphone, an audio representation of the one or more wake-up words; determining a strength of the audio representation of the one or more wake-up words based on one or more dynamic measures; and providing a message on a display device, wherein the message comprises one or more improvements to a likelihood that the speech recognizer recognizes the one or more wake-up words based on the strengths of the text and audio representations. 3. The method of claim 1 , wherein the determining the strength of the text representation of the one or more wake-up words comprises determining a number of syllables in the one or more wake-up words or determining a number of phonologically different groups of phonemes associated with the one or more wake-up words. | 0.7 |
8,612,229 | 19 | 22 | 19. An apparatus for facilitating development of a computer-implemented natural language understanding (NLU) model associated with an NLU application, the apparatus comprising: at least one computer-readable medium encoded with instructions; and at least one processing unit coupled to the at least one computer-readable medium, wherein upon execution of the instructions by the at least one processing unit, the at least one processing unit: receives, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determines whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selects the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: adds the at least one expected user entry to an NLU entry data set associated with the NLU model, and trains the NLU model to associate the at least one expected user entry with the desired routing destination. | 19. An apparatus for facilitating development of a computer-implemented natural language understanding (NLU) model associated with an NLU application, the apparatus comprising: at least one computer-readable medium encoded with instructions; and at least one processing unit coupled to the at least one computer-readable medium, wherein upon execution of the instructions by the at least one processing unit, the at least one processing unit: receives, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determines whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selects the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: adds the at least one expected user entry to an NLU entry data set associated with the NLU model, and trains the NLU model to associate the at least one expected user entry with the desired routing destination. 22. The apparatus of claim 19 , wherein the at least one processing unit: increases a statistical weighting of the at least one expected user entry relative to another entry in the NLU data entry set. | 0.808061 |
10,152,474 | 1 | 4 | 1. A device, comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, to: obtain a document, the document including a set of words or a set of characters; identify a skip value for the document, the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determine one or more skip n-grams using the skip value for the document, a skip n-gram, of the one or more skip n-grams, including a sequence of one or more words or one or more characters with a plurality of occurrences in the document, the sequence of one or more words or one or more characters including a skip value quantity of words or characters within the sequence; extract one or more terms from the document based on the one or more skip n-grams, a term associated with the skip n-gram corresponding to the skip value quantity of words or characters within the sequence; generate a functional diagram representing the document using the one or more terms based on extracting the one or more terms; and provide, via a user interface, information identifying the functional diagram. | 1. A device, comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, to: obtain a document, the document including a set of words or a set of characters; identify a skip value for the document, the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determine one or more skip n-grams using the skip value for the document, a skip n-gram, of the one or more skip n-grams, including a sequence of one or more words or one or more characters with a plurality of occurrences in the document, the sequence of one or more words or one or more characters including a skip value quantity of words or characters within the sequence; extract one or more terms from the document based on the one or more skip n-grams, a term associated with the skip n-gram corresponding to the skip value quantity of words or characters within the sequence; generate a functional diagram representing the document using the one or more terms based on extracting the one or more terms; and provide, via a user interface, information identifying the functional diagram. 4. The device of claim 1 , where the one or more processors are further to: determine that the skip n-gram satisfies a threshold quantity of repetitions in the document; and where the one or more processors, when extracting the one or more terms from the document, are to: extract the term from the document based on determining that the skip n-gram satisfies the threshold quantity of repetitions. | 0.710335 |
8,578,171 | 29 | 30 | 29. The computer-readable storage medium of claim 25 , wherein the particular organization represents a category, wherein users internal to the particular organization are included in the category and wherein users external to the particular organization are not included in the category. | 29. The computer-readable storage medium of claim 25 , wherein the particular organization represents a category, wherein users internal to the particular organization are included in the category and wherein users external to the particular organization are not included in the category. 30. The computer-readable storage medium of claim 29 , wherein the category is one of personal, customer, and supplier. | 0.947252 |
7,853,555 | 1 | 5 | 1. A method to query multilingual data, the method comprising: receiving a request for a query using a computer, the query comprising a base word in a source language used for a search of a database in a target language; applying, using the computer, the request to factors, the factors comprising: an interface factor to indicate a speed of a connection between a set of components, the components comprising: multilingual service components; and core enterprise services components; a component availability factor to indicate the availability of the components; a language identification factor to indicate the source language, a required speed factor indicating an amount of time required by a user for the query to return a result, a required quality factor, and a user language fluency factor, selecting a subset of the components based on the factors using the computer; and performing the query using the computer based on the subset of the components, wherein performing the query comprises determining a word ontology of the base word in the source language, and wherein determining the word ontology of the base word comprises determining synonyms, homonyms, hypernyms and hyponyms of the base word. | 1. A method to query multilingual data, the method comprising: receiving a request for a query using a computer, the query comprising a base word in a source language used for a search of a database in a target language; applying, using the computer, the request to factors, the factors comprising: an interface factor to indicate a speed of a connection between a set of components, the components comprising: multilingual service components; and core enterprise services components; a component availability factor to indicate the availability of the components; a language identification factor to indicate the source language, a required speed factor indicating an amount of time required by a user for the query to return a result, a required quality factor, and a user language fluency factor, selecting a subset of the components based on the factors using the computer; and performing the query using the computer based on the subset of the components, wherein performing the query comprises determining a word ontology of the base word in the source language, and wherein determining the word ontology of the base word comprises determining synonyms, homonyms, hypernyms and hyponyms of the base word. 5. The method of claim 1 wherein applying the request to the factors further comprising: a presence of an index. | 0.898551 |
8,417,651 | 9 | 12 | 9. A computer based method of matching a text description to a structured record of a product, the method comprising: obtaining a set of text descriptions and a set of structured records individually containing a plurality of attributes of a product, each of the text descriptions matching one of the structured records; parsing the set of text descriptions to form one or more text segments; associating the text segments of each text description with one or more attributes of the structured records; and deriving a weight factor for at least some of the associated attributes based on matches of the individual text descriptions to one of the structured records, the weight factor representing a relative importance of the corresponding attributes for matching. | 9. A computer based method of matching a text description to a structured record of a product, the method comprising: obtaining a set of text descriptions and a set of structured records individually containing a plurality of attributes of a product, each of the text descriptions matching one of the structured records; parsing the set of text descriptions to form one or more text segments; associating the text segments of each text description with one or more attributes of the structured records; and deriving a weight factor for at least some of the associated attributes based on matches of the individual text descriptions to one of the structured records, the weight factor representing a relative importance of the corresponding attributes for matching. 12. The method of claim 9 wherein each of the attributes is associated with a corresponding value, and wherein: parsing the text descriptions includes parsing each of the text descriptions into a plurality of text segments, at least two of the text segments overlapping each other; associating each of the text segments includes associating each of the text segments with more than one of the attributes; and the method further includes, for each of the text description, selecting one attribute from the more than one associated attributes as an associated attribute for the text description based on the values of the more than one attributes in the text description and in the structured record. | 0.734802 |
8,943,090 | 14 | 15 | 14. A system, comprising: a processor; memory including instructions that, upon being executed by the processor, cause the system to: identify query descriptors for query content of a search request, the query descriptors characterizing the query content; for each content piece of at least a portion of a content collection: identify a subset of content descriptors of the content piece that corresponds to at least a portion of the query descriptors, the content descriptors characterizing the content piece, one or more of the subset of the content descriptors corresponding to one or more blur transforms; identify first candidate regions of the content piece, one or more of the first candidate regions overlapping with at least another one of the first candidate regions, each first candidate region corresponding to at least a portion of the subset of the content descriptors; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the first candidate regions comprises a first proportionate size greater than a first proportion threshold; and provide the matching content subset in response to the search request. | 14. A system, comprising: a processor; memory including instructions that, upon being executed by the processor, cause the system to: identify query descriptors for query content of a search request, the query descriptors characterizing the query content; for each content piece of at least a portion of a content collection: identify a subset of content descriptors of the content piece that corresponds to at least a portion of the query descriptors, the content descriptors characterizing the content piece, one or more of the subset of the content descriptors corresponding to one or more blur transforms; identify first candidate regions of the content piece, one or more of the first candidate regions overlapping with at least another one of the first candidate regions, each first candidate region corresponding to at least a portion of the subset of the content descriptors; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the first candidate regions comprises a first proportionate size greater than a first proportion threshold; and provide the matching content subset in response to the search request. 15. The system of claim 14 , wherein the instructions, upon being executed, further cause the system to: identify second candidate regions of the content piece; and select the content piece for inclusion in the matching content subset when at least one of the second candidate regions comprises a second proportionate size greater than a second proportion threshold. | 0.738197 |
9,984,147 | 1 | 4 | 1. A method of clustering a set of objects having respective object types, respective object attributes, homogeneous relationships between respective objects of the same object type, and heterogeneous relationships between objects having a different object types, the method comprising: iteratively optimizing a clustering of the set of objects within a plurality of latent classes, dependent on object type, object attributes, homogeneous relationships, and heterogeneous relationships, by performing: in an expectation step, updating a set of posteriors to maximize a probability that an object is associated with a respective latent class comprising, for each object, individually fixing an assigned latent class for all other objects, and maximizing an objective function for the respective object, comprising minimizing a computed distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of a corresponding expectation that the object is associated with the respective latent class, and repeating until no object changes in assigned latent class between successive repetition, and in a minimization step, updating the plurality of latent classes based on the updated set of posteriors; and storing the optimized clustering. | 1. A method of clustering a set of objects having respective object types, respective object attributes, homogeneous relationships between respective objects of the same object type, and heterogeneous relationships between objects having a different object types, the method comprising: iteratively optimizing a clustering of the set of objects within a plurality of latent classes, dependent on object type, object attributes, homogeneous relationships, and heterogeneous relationships, by performing: in an expectation step, updating a set of posteriors to maximize a probability that an object is associated with a respective latent class comprising, for each object, individually fixing an assigned latent class for all other objects, and maximizing an objective function for the respective object, comprising minimizing a computed distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of a corresponding expectation that the object is associated with the respective latent class, and repeating until no object changes in assigned latent class between successive repetition, and in a minimization step, updating the plurality of latent classes based on the updated set of posteriors; and storing the optimized clustering. 4. The method according to claim 1 , wherein the posteriors are computed using a Gibbs sampler. | 0.930657 |
5,495,558 | 7 | 8 | 7. The fuzzy inference development system of claim 1, wherein each of said plurality of inference engines, comprises: a rule processing module which stipulates how specified rules are to be processed; and a membership function processing module which includes: a description module for defining designated membership functions; and a goodness of fit calculating module for calculating a goodness of fit input data for a plurality of membership functions. | 7. The fuzzy inference development system of claim 1, wherein each of said plurality of inference engines, comprises: a rule processing module which stipulates how specified rules are to be processed; and a membership function processing module which includes: a description module for defining designated membership functions; and a goodness of fit calculating module for calculating a goodness of fit input data for a plurality of membership functions. 8. The fuzzy inference development system of claim 7, wherein said rule processing module and said membership function processing module for said plurality of inference engines are stored in said inference engine memory. | 0.902655 |
9,081,767 | 9 | 11 | 9. A non-transitory computer readable medium configured to store instructions for browsing a datastore of data objects, the instructions when executed by a processor perform steps comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence. | 9. A non-transitory computer readable medium configured to store instructions for browsing a datastore of data objects, the instructions when executed by a processor perform steps comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence. 11. The non-transitory computer readable medium of claim 9 , wherein providing the second sentence for display comprises providing the second sentence for display with an object that is a generic object, the generic object representing a plurality of data objects. | 0.635359 |
7,533,077 | 9 | 13 | 9. A system for automatically creating managed resources, comprising: a computer, including: a definition file system for automatically reading a definition file that is a global set of definitions for all managed resources that can be created, each definition of the global set of definitions having a defined syntax for describing functions and attributes for an individual managed object after a process is started; an object file system for automatically reading an object file that is a description of a single desired managed object after the process is started; a validation system for automatically validating the description in the object file using a defined syntax of a definition in the definition file corresponding to the single desired managed object after the definition file and the object file are read, wherein the validating ensures that the description within the object file is in the appropriate format as that in the definition file; a resource system for automatically creating a new managed resource by the process, wherein the created new managed resource is based on the validated description immediately following the validating, wherein the new managed resource is designed to be managed by a separate program, the separate program automatically facilitating any generation and implementation of a management request; and a tagging system for automatically tagging the new managed resource with an address tag corresponding to the process, wherein the address tag specifically identifies the process and, wherein object header of the single desired managed object created by the new managed resource includes the address tag. | 9. A system for automatically creating managed resources, comprising: a computer, including: a definition file system for automatically reading a definition file that is a global set of definitions for all managed resources that can be created, each definition of the global set of definitions having a defined syntax for describing functions and attributes for an individual managed object after a process is started; an object file system for automatically reading an object file that is a description of a single desired managed object after the process is started; a validation system for automatically validating the description in the object file using a defined syntax of a definition in the definition file corresponding to the single desired managed object after the definition file and the object file are read, wherein the validating ensures that the description within the object file is in the appropriate format as that in the definition file; a resource system for automatically creating a new managed resource by the process, wherein the created new managed resource is based on the validated description immediately following the validating, wherein the new managed resource is designed to be managed by a separate program, the separate program automatically facilitating any generation and implementation of a management request; and a tagging system for automatically tagging the new managed resource with an address tag corresponding to the process, wherein the address tag specifically identifies the process and, wherein object header of the single desired managed object created by the new managed resource includes the address tag. 13. The system of claim 9 , wherein the object file is an XML file, and wherein the defined syntax in the definition file is in XML. | 0.528571 |
7,623,711 | 27 | 49 | 27. A computer-readable storage medium having instructions stored therein, which when executed by a system, cause the system to perform a method comprising: identifying spatial relationships between document objects of a document image; determining space separating pairs of neighboring document objects, wherein the space separating pairs of neighboring document objects is represented as weights in a weighted graph model; and determining a scaling factor based on the space separating the document objects in the document image and based on display device characteristics. | 27. A computer-readable storage medium having instructions stored therein, which when executed by a system, cause the system to perform a method comprising: identifying spatial relationships between document objects of a document image; determining space separating pairs of neighboring document objects, wherein the space separating pairs of neighboring document objects is represented as weights in a weighted graph model; and determining a scaling factor based on the space separating the document objects in the document image and based on display device characteristics. 49. The computer-readable storage medium defined in claim 27 wherein the method further comprises storing the graph as metadata in a JPM file that contains the document objects. | 0.798405 |
9,685,174 | 1 | 2 | 1. A method of detecting a speech-identifiable condition of a subject, the method comprising: recording speech data of the subject via a communication device input that receives the speech data for the subject while not receiving speech data for anyone else talking to the subject; transmitting, by the communication device, the recorded speech data to a mood detection machine that includes a feature extraction module and a decision module; performing, in the feature extraction module, a low-level feature extraction on the speech data over a plurality of short-time segments to develop low-level feature data; performing, in the feature extraction module, a segment-level feature extraction on the low-level feature data over a window of time to develop segment-level feature data, where the window of time comprises the plurality of short time segments, and wherein the low-level feature extraction combined with the segment-level feature extraction masks out words contained in the speech data such that the segment-level feature data is non-lexical data; applying the segment-level feature data to the decision module that includes a database of one or more classifiers, each classifier from among the classifiers corresponding to a different classification of the speech-identifiable condition; and determining, in the decision module, the classification of the speech-identifiable condition of the subject from the segment-level feature data. | 1. A method of detecting a speech-identifiable condition of a subject, the method comprising: recording speech data of the subject via a communication device input that receives the speech data for the subject while not receiving speech data for anyone else talking to the subject; transmitting, by the communication device, the recorded speech data to a mood detection machine that includes a feature extraction module and a decision module; performing, in the feature extraction module, a low-level feature extraction on the speech data over a plurality of short-time segments to develop low-level feature data; performing, in the feature extraction module, a segment-level feature extraction on the low-level feature data over a window of time to develop segment-level feature data, where the window of time comprises the plurality of short time segments, and wherein the low-level feature extraction combined with the segment-level feature extraction masks out words contained in the speech data such that the segment-level feature data is non-lexical data; applying the segment-level feature data to the decision module that includes a database of one or more classifiers, each classifier from among the classifiers corresponding to a different classification of the speech-identifiable condition; and determining, in the decision module, the classification of the speech-identifiable condition of the subject from the segment-level feature data. 2. The method of claim 1 , wherein the speech-identifiable condition is a mood state of the subject. | 0.860724 |
9,646,230 | 11 | 12 | 11. The method of claim 10 , further comprising upon generating the additional image portions corresponding to the segmented image portion, determining if the respective additional image portions exceed the expected maximum width. | 11. The method of claim 10 , further comprising upon generating the additional image portions corresponding to the segmented image portion, determining if the respective additional image portions exceed the expected maximum width. 12. The method of claim 11 , further comprising upon determining that one of the additional image portions exceeds the expected maximum width, using the trained neural network to analyze the additional image portion. | 0.925052 |
8,543,981 | 1 | 5 | 1. A method for editing a test script for testing software comprising: a processor in communication with a database, the processor configured for: providing an application state stack that includes a plurality of consecutive states, each application state includes at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods, the test methods being associated with state transitions; receiving a request to modify the test script; creating a modified application state stack portion based on the modified test script; checking the integrity of the modified test script by ensuring that the modified application state stack portion can be integrated with at least a portion of the application state stack subsequent to the modified portion by analyzing the state transitions associated with test methods; and if the modified test script maintains integrity, allowing the modified test script to replace the test script and updating the application state stack with the application state stack integrated with the modified portion of the application state stack. | 1. A method for editing a test script for testing software comprising: a processor in communication with a database, the processor configured for: providing an application state stack that includes a plurality of consecutive states, each application state includes at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods, the test methods being associated with state transitions; receiving a request to modify the test script; creating a modified application state stack portion based on the modified test script; checking the integrity of the modified test script by ensuring that the modified application state stack portion can be integrated with at least a portion of the application state stack subsequent to the modified portion by analyzing the state transitions associated with test methods; and if the modified test script maintains integrity, allowing the modified test script to replace the test script and updating the application state stack with the application state stack integrated with the modified portion of the application state stack. 5. The method of claim 1 , wherein the test script is modified by deleting a consecutive sequence of actions from the test script. | 0.503817 |
8,185,589 | 21 | 26 | 21. A computer program product for use at a computer system, the computer program product for implementing a method for presenting message conversation data, the computer program product comprising one or more computer-readable storage device having stored thereon computer-executable instructions that, when executed by a processor, cause the computer system to perform the method of claim 7 . | 21. A computer program product for use at a computer system, the computer program product for implementing a method for presenting message conversation data, the computer program product comprising one or more computer-readable storage device having stored thereon computer-executable instructions that, when executed by a processor, cause the computer system to perform the method of claim 7 . 26. The computer program product as recited in claim 21 , wherein computer-executable instructions that when executed cause the computer system to retrieve persisted conversation attribute values from the electronic mail conversation item comprise computer-executable instructions that when executed cause the computer system to retrieve one or more attribute values for an electronic mail message selected from among a sent time value, a sender value, a summary value, a link value, and a recipient delta value. | 0.922188 |
8,056,128 | 53 | 55 | 53. A computer-readable memory device containing instructions for controlling at least one processor to perform a method, the computer-readable memory device storing one or more instructions for: identifying a document in a ranked set of documents as being suspect based on whether the document requests personal or private information from a user, where documents in the set of ranked documents that are well known are ranked higher than documents that are not well known; analyzing data or attributes associated with the suspect document, where analyzing data or attributes associated with the suspect document includes analyzing a ranking of the suspect document relative to rankings of other documents in the set of ranked documents; assigning a fraud score, based on the analyzed data or attributes, to the suspect document; comparing the fraud score to a first threshold and to a second different threshold; determining that the suspect document is trustworthy when the fraud score does not pass the first threshold; determining that the suspect document is untrustworthy when the fraud score passes the second different threshold; obtaining a determination of trustworthiness from a user when the fraud score is between the first threshold and the second different threshold; and storing an identifier for the suspect document, the fraud score, and a designation of a trustworthiness of the suspect document in a memory. | 53. A computer-readable memory device containing instructions for controlling at least one processor to perform a method, the computer-readable memory device storing one or more instructions for: identifying a document in a ranked set of documents as being suspect based on whether the document requests personal or private information from a user, where documents in the set of ranked documents that are well known are ranked higher than documents that are not well known; analyzing data or attributes associated with the suspect document, where analyzing data or attributes associated with the suspect document includes analyzing a ranking of the suspect document relative to rankings of other documents in the set of ranked documents; assigning a fraud score, based on the analyzed data or attributes, to the suspect document; comparing the fraud score to a first threshold and to a second different threshold; determining that the suspect document is trustworthy when the fraud score does not pass the first threshold; determining that the suspect document is untrustworthy when the fraud score passes the second different threshold; obtaining a determination of trustworthiness from a user when the fraud score is between the first threshold and the second different threshold; and storing an identifier for the suspect document, the fraud score, and a designation of a trustworthiness of the suspect document in a memory. 55. The computer-readable memory device of claim 53 , where analyzing data or attributes associated with the suspect document further comprises: analyzing a content of the suspect document to determine if the suspect document has characteristics of known fraudulent documents. | 0.947368 |
9,400,789 | 10 | 11 | 10. The system of claim 9 , wherein the operations further comprise: receiving a selection of one or more of the first document groups; and in response to receiving the selection, including data identifying the one or more selected first document groups in the author profile for the author as documents authored by the author. | 10. The system of claim 9 , wherein the operations further comprise: receiving a selection of one or more of the first document groups; and in response to receiving the selection, including data identifying the one or more selected first document groups in the author profile for the author as documents authored by the author. 11. The system of claim 10 , wherein the operations further comprise: clustering a plurality of second documents into one or more second document groups, wherein each of the one or more second document groups is associated with a respective author proper name; for each of the one or more second document groups: determining a correspondence score for the second document group in reference to the author profile for the author; determining whether or not the correspondence score satisfies a threshold; and when the correspondence score satisfies the threshold, including data identifying the second documents in the second document group as documents authored by the author in the author profile for the author. | 0.82711 |
6,012,052 | 6 | 7 | 6. The method of claim 1 wherein the step of determining resource transition probabilities based on the identification of users, the identification of resources, and the defined sessions includes sub-steps of: i) counting a number of times that a first resource was referenced to generate a first count; ii) counting a number of times that a second resource was referenced after the first resource was referenced to generate a second count; and iii) determining a transition probability from the first resource to the second resource based on the first and second counts. | 6. The method of claim 1 wherein the step of determining resource transition probabilities based on the identification of users, the identification of resources, and the defined sessions includes sub-steps of: i) counting a number of times that a first resource was referenced to generate a first count; ii) counting a number of times that a second resource was referenced after the first resource was referenced to generate a second count; and iii) determining a transition probability from the first resource to the second resource based on the first and second counts. 7. The method of claim 6 wherein the second count is decreased when a transition from the first resource to the second resource is possible but does not occur. | 0.907451 |
9,569,593 | 84 | 85 | 84. The at least one non-transitory computer-readable storage medium of claim 61 , wherein the generating is performed using at least one model trained on past surgical reports. | 84. The at least one non-transitory computer-readable storage medium of claim 61 , wherein the generating is performed using at least one model trained on past surgical reports. 85. The at least one non-transitory computer-readable storage medium of claim 84 , wherein the at least one model is specific to one of the one or more clinical personnel who authorizes the text report. | 0.957687 |
9,918,132 | 2 | 3 | 2. The pattern code recognition multimedia playback system according to claim 1 , wherein the pattern code recognition pen determines a property of data indicating the pattern code, extracts, when it is determined that the property of the data is an audio, audio data corresponding to the pattern code from a memory included in the pattern code recognition pen and playback the audio data, and transmits, when it is determined that the property of the data is not an audio, the pattern code to the pattern code recognition set-top box. | 2. The pattern code recognition multimedia playback system according to claim 1 , wherein the pattern code recognition pen determines a property of data indicating the pattern code, extracts, when it is determined that the property of the data is an audio, audio data corresponding to the pattern code from a memory included in the pattern code recognition pen and playback the audio data, and transmits, when it is determined that the property of the data is not an audio, the pattern code to the pattern code recognition set-top box. 3. The pattern code recognition multimedia playback system according to claim 2 , wherein the pattern code recognition pen determines whether or not the property of the data is an audio based on whether or not the audio data corresponding to the pattern code is stored in the memory. | 0.912546 |
9,984,048 | 1 | 7 | 1. A system, comprising: one or more processors configured to: receive a search query input at a search box from a user; and in response to the search query: obtain historical user operation data associated with the user; generate a plurality of navigation hierarchical structure diagrams based on a website navigation category diagram and the historical user operation data associated with the user, wherein: the website navigation category diagram comprises a plurality of nodes; the plurality of navigation hierarchical structure diagrams comprises a first navigation hierarchical structure diagram and a second navigation hierarchical structure diagram, wherein the first navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams is generated based at least in part on one or more of the following binding conditions: nodes associated with the first navigation hierarchical structure diagram with a corresponding confidence level greater than a preset threshold value are included in a predetermined level of the first navigation hierarchical structure diagram; a total number of nodes in a level of the first navigation hierarchical structure diagram is no greater than a number of nodes for which associated information is permitted to be displayed at a web page; and for a particular node that appears more frequently in the first navigation hierarchical structure diagram more than a substantially similar node appears at the website navigation category diagram, at least one copy of that particular node is eliminated; the first navigation hierarchical structure diagram comprises a first at least subset of the plurality of nodes and the second navigation hierarchical structure diagram comprises a second at least subset of the plurality of nodes; and each of the first at least subset of the plurality of nodes and the second at least subset of the plurality of nodes is different from the website navigation category diagram; determine a plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams based at least in part on the historical user operation data associated with the user; select a selected navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams based on the plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams; and implement at least in part a website navigation process using the selected navigation hierarchical structure diagram; and one or more memories coupled to the one or more processors and configured to provide instructions to the one or more processors. | 1. A system, comprising: one or more processors configured to: receive a search query input at a search box from a user; and in response to the search query: obtain historical user operation data associated with the user; generate a plurality of navigation hierarchical structure diagrams based on a website navigation category diagram and the historical user operation data associated with the user, wherein: the website navigation category diagram comprises a plurality of nodes; the plurality of navigation hierarchical structure diagrams comprises a first navigation hierarchical structure diagram and a second navigation hierarchical structure diagram, wherein the first navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams is generated based at least in part on one or more of the following binding conditions: nodes associated with the first navigation hierarchical structure diagram with a corresponding confidence level greater than a preset threshold value are included in a predetermined level of the first navigation hierarchical structure diagram; a total number of nodes in a level of the first navigation hierarchical structure diagram is no greater than a number of nodes for which associated information is permitted to be displayed at a web page; and for a particular node that appears more frequently in the first navigation hierarchical structure diagram more than a substantially similar node appears at the website navigation category diagram, at least one copy of that particular node is eliminated; the first navigation hierarchical structure diagram comprises a first at least subset of the plurality of nodes and the second navigation hierarchical structure diagram comprises a second at least subset of the plurality of nodes; and each of the first at least subset of the plurality of nodes and the second at least subset of the plurality of nodes is different from the website navigation category diagram; determine a plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams based at least in part on the historical user operation data associated with the user; select a selected navigation hierarchical structure diagram of the plurality of navigation hierarchical structure diagrams based on the plurality of searching costs corresponding to respective ones of the plurality of navigation hierarchical structure diagrams; and implement at least in part a website navigation process using the selected navigation hierarchical structure diagram; and one or more memories coupled to the one or more processors and configured to provide instructions to the one or more processors. 7. The system of claim 1 , wherein the one or more processors are further configured to determine a confidence level for each of the first at least a subset of the plurality of nodes associated with the website navigation category diagram based at least in part on the historical user operation data associated with the user. | 0.839585 |
7,831,951 | 32 | 34 | 32. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform the method, comprising: optimizing a description of the functionality and timing of a digital system, wherein the description comprises a plurality of tasks, wherein optimizing includes separately performing design-time intra-task scheduling for at least two of the tasks to generate a plurality of intra-task schedules for each of the tasks, wherein the plurality of intra-task schedules are a subset of all possible intra-task schedules, and wherein the subset defines partly task trade-off optimization information. | 32. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform the method, comprising: optimizing a description of the functionality and timing of a digital system, wherein the description comprises a plurality of tasks, wherein optimizing includes separately performing design-time intra-task scheduling for at least two of the tasks to generate a plurality of intra-task schedules for each of the tasks, wherein the plurality of intra-task schedules are a subset of all possible intra-task schedules, and wherein the subset defines partly task trade-off optimization information. 34. The program storage device of claim 32 , wherein the description comprises a system-level description wherein non-deterministic behavior of the digital system is modeled by interacting the tasks, while each of the tasks describe part of the deterministic behavior of the digital system. | 0.689507 |
8,977,248 | 12 | 15 | 12. A method of processing a voice communication and enabling a first user to share information with other users, comprising: translating some or all of a voice communication, including a plurality of spoken words, from the first user to text using at least in part a speech-to-text recognizer; creating a text message from a selected portion of the translated text based at least in part on: an identification of one or more words in the translated text that correspond to respective one or more words in a vocabulary of uncommon words that are uncommon in voice communications, and transmitting, by a processing system, the text message from the translated text to a social networking for posting on a social networking web page, wherein the social networking web page is configured to share first user information posted on the social networking web page with others. | 12. A method of processing a voice communication and enabling a first user to share information with other users, comprising: translating some or all of a voice communication, including a plurality of spoken words, from the first user to text using at least in part a speech-to-text recognizer; creating a text message from a selected portion of the translated text based at least in part on: an identification of one or more words in the translated text that correspond to respective one or more words in a vocabulary of uncommon words that are uncommon in voice communications, and transmitting, by a processing system, the text message from the translated text to a social networking for posting on a social networking web page, wherein the social networking web page is configured to share first user information posted on the social networking web page with others. 15. The method as defined in claim 12 , the method further comprising: detecting that the first user is speaking in such a manner as to interfere with an acceptable conversion of the voice communication to text; and playing a message to the first user, the message requesting the first user change the first user's speaking manner. | 0.75 |
8,947,355 | 12 | 14 | 12. The computer-implemented method of claim 5 , wherein the graphical user interface provides at least two modes of control over the rate of movement of the selection element. | 12. The computer-implemented method of claim 5 , wherein the graphical user interface provides at least two modes of control over the rate of movement of the selection element. 14. The computer-implemented method of claim 12 , wherein the electronic device comprises a touch sensitive material over at least a portion of an exterior of the electronic device, the user being able to provide a variety of inputs with respect to the graphical user interface using a plurality of different motions with respect to the touch sensitive material. | 0.918652 |
4,718,094 | 71 | 77 | 71. A method of evaluating the likelihood of a word corresponding to a speech input in a speech-recognition system comprising the steps of: for a subject word in a vocabulary of words, generating a first word score representing the subject word likelihood based on an acoustic match first algorithm; for the subject word, generating a second word score based on a second independent algorithm which differs from the first algorithm; and forming a total word score for the subject word from at least the first word score and the second word score. | 71. A method of evaluating the likelihood of a word corresponding to a speech input in a speech-recognition system comprising the steps of: for a subject word in a vocabulary of words, generating a first word score representing the subject word likelihood based on an acoustic match first algorithm; for the subject word, generating a second word score based on a second independent algorithm which differs from the first algorithm; and forming a total word score for the subject word from at least the first word score and the second word score. 77. The method of claim 71 wherein the step of generating the second word score includes the steps of: generating acoustic labels in response to the uttering of speech inputs wherein each label identifies a respective class of speech input, the classes being based on predefined speech input features; and forming a first table in which each label in the alphabet provides a vote for each word in the vocabulary, each label vote for a subject word indicating the likelihood of the subject word producing the label providing the vote; forming a second table in which each label is assigned a penalty for each word in the vocabulary, the penalty assigned to a given label for a given word being indicative of the likelihood of the given label not being produced according to the model for the given word; for a given string of generated labels, determining a polled word score for a subject word which includes the step of combining the respective votes and penalties of all labels in the string for the subject word, the polled word score being the second word score. | 0.675198 |
8,161,112 | 1 | 8 | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; acquiring data representing a client's environmental condition; storing, in the context server in a data structure comprising a dynamic client context for the client, the data representing a client's environmental condition; detecting an event in dependence upon the dynamic client context; identifying one or more collaborators in dependence upon the dynamic client context and the event; selecting from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators; and transmitting the selected classified structural element to the collaborator. | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; acquiring data representing a client's environmental condition; storing, in the context server in a data structure comprising a dynamic client context for the client, the data representing a client's environmental condition; detecting an event in dependence upon the dynamic client context; identifying one or more collaborators in dependence upon the dynamic client context and the event; selecting from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators; and transmitting the selected classified structural element to the collaborator. 8. The method of claim 1 wherein identifying the one or more collaborators further comprises identifying the collaborator in dependence upon collaborator presence on a instant messaging network. | 0.919435 |
9,251,279 | 37 | 40 | 37. A computer system comprising: a database having a plurality of records in respective categories of information, each record having one or more facets to the respective category of information; means for receiving user input of a first search term formed of a first parameter indicative of at least one category of information of the database; a search engine to implement a search of the database for records of the at least one category of information; means for displaying, in response to the user input of the first search term, simultaneously displaying both in a same screen view: (a) a set of search results, including records from the database of the at least one category of information, and (b) a listing of any one or combination of facets and facet values of the records in the set of search results, the listing serving as suggested additional parameters for further refining the first search term upon user selection of the any one or combination of facets and facet values, wherein at least one of the any one or combination of facets and facet values is defined by a community of users and corresponds to content generated by the community of users; means for enabling user input of a second search term formed of a second parameter; and a refinement engine for refining the search based on the listing and additional user input or the second search term. | 37. A computer system comprising: a database having a plurality of records in respective categories of information, each record having one or more facets to the respective category of information; means for receiving user input of a first search term formed of a first parameter indicative of at least one category of information of the database; a search engine to implement a search of the database for records of the at least one category of information; means for displaying, in response to the user input of the first search term, simultaneously displaying both in a same screen view: (a) a set of search results, including records from the database of the at least one category of information, and (b) a listing of any one or combination of facets and facet values of the records in the set of search results, the listing serving as suggested additional parameters for further refining the first search term upon user selection of the any one or combination of facets and facet values, wherein at least one of the any one or combination of facets and facet values is defined by a community of users and corresponds to content generated by the community of users; means for enabling user input of a second search term formed of a second parameter; and a refinement engine for refining the search based on the listing and additional user input or the second search term. 40. A system as claimed in claim 37 , wherein the listing of facet values is by facet value count and kind, a facet value count being a count of the entries being described with that facet value. | 0.885831 |
8,380,502 | 10 | 11 | 10. A device comprising: a memory to store instructions; and at least one processor to execute the instructions to: receive a voice search query from a user, derive a plurality of recognition hypotheses from the voice search query, determine a plurality of scores associated with the plurality of recognition hypotheses, the at least one processor determining the plurality of scores based on a comparison of the plurality of recognition hypotheses to previously received search queries, discard at least one of the plurality of recognition hypotheses, that is associated with at least one first score, of the plurality of scores, that is less than a threshold value, construct a first query using at least one first non-discarded recognition hypothesis of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, the at least one processor, when constructing the first query, being further to: form an initial query based on the at least one first non-discarded recognition hypothesis, identify a plurality of stop words in the initial query, and prune, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold, forward the first query to a search system, receive, from the search system, first results associated with the first query, and provide, to the user, the first results. | 10. A device comprising: a memory to store instructions; and at least one processor to execute the instructions to: receive a voice search query from a user, derive a plurality of recognition hypotheses from the voice search query, determine a plurality of scores associated with the plurality of recognition hypotheses, the at least one processor determining the plurality of scores based on a comparison of the plurality of recognition hypotheses to previously received search queries, discard at least one of the plurality of recognition hypotheses, that is associated with at least one first score, of the plurality of scores, that is less than a threshold value, construct a first query using at least one first non-discarded recognition hypothesis of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, the at least one processor, when constructing the first query, being further to: form an initial query based on the at least one first non-discarded recognition hypothesis, identify a plurality of stop words in the initial query, and prune, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold, forward the first query to a search system, receive, from the search system, first results associated with the first query, and provide, to the user, the first results. 11. The device of claim 10 , where the at least one processor, when deriving the plurality of recognition hypotheses from the voice search query, is further to: use at least one of a language model, a phonetic dictionary, or an acoustic model to derive the plurality of recognition hypotheses. | 0.898122 |
9,922,650 | 16 | 17 | 16. The system of claim 6 , wherein the decoding graph comprises a plurality of metadata tags, wherein a first metadata tag of the plurality of metadata tags represents the first intent and is associated with the first path, wherein a second metadata tag of the plurality of metadata tags represents the first intent and is associated with the second path, and wherein a third metadata tag of the plurality of metadata tags represents the second intent and is associated with the third path. | 16. The system of claim 6 , wherein the decoding graph comprises a plurality of metadata tags, wherein a first metadata tag of the plurality of metadata tags represents the first intent and is associated with the first path, wherein a second metadata tag of the plurality of metadata tags represents the first intent and is associated with the second path, and wherein a third metadata tag of the plurality of metadata tags represents the second intent and is associated with the third path. 17. The system of claim 16 , wherein the one or more processors are further programmed by the executable instructions to determine, using the second metadata tag, that the second path is associated with the first intent. | 0.951478 |
7,577,561 | 1 | 7 | 1. A computer-implemented method of generating a target language localized template, the method comprising: creating a source language markup language (ML) text template based on a source language text string, said source language ML text template including at least one token, wherein the at least one token includes: a token operator assigned to a variable text element included in the source language text string, wherein a first symbol is designated as said token operator, and wherein the first symbol corresponds to a predefined source language grammar rule, and a token operand assigned to the variable text element, wherein a second symbol is designated as said token operand, and wherein the second symbol corresponds to a predefined context type; translating one or more words in the source language ML text template to one or more words in a target language so as to generate a target language ML text template, wherein the target language ML text template is generated by at least one translation tool residing in at least one of a client computer and a server computer; wherein said target language ML text template includes said token operator; and defining the target language localized template for the target language ML text template using the translated words. | 1. A computer-implemented method of generating a target language localized template, the method comprising: creating a source language markup language (ML) text template based on a source language text string, said source language ML text template including at least one token, wherein the at least one token includes: a token operator assigned to a variable text element included in the source language text string, wherein a first symbol is designated as said token operator, and wherein the first symbol corresponds to a predefined source language grammar rule, and a token operand assigned to the variable text element, wherein a second symbol is designated as said token operand, and wherein the second symbol corresponds to a predefined context type; translating one or more words in the source language ML text template to one or more words in a target language so as to generate a target language ML text template, wherein the target language ML text template is generated by at least one translation tool residing in at least one of a client computer and a server computer; wherein said target language ML text template includes said token operator; and defining the target language localized template for the target language ML text template using the translated words. 7. The method of claim 1 , wherein the predefined context type comprises at least one of number, gender, type, honor, age, and faction. | 0.922503 |
9,171,066 | 4 | 5 | 4. The method of claim 1 , further comprising ranking, by the server, the second set of interpretation candidates. | 4. The method of claim 1 , further comprising ranking, by the server, the second set of interpretation candidates. 5. The method of claim 4 , further comprising configuring the client device to re-rank the second set of interpretation candidates. | 0.965215 |
9,704,477 | 7 | 11 | 7. A non-transitory computer-readable medium having processor-executable instructions stored thereon for providing text-to-speech (TTS) functionality to a telematics unit of a telematics-equipped vehicle in a networked system, the processor-executable instructions, when executed by a processor of the telematics unit or a remote TTS engine on a remote server, facilitating performance of the following steps: receiving text content to be played back by an audio system of the telematics-equipped vehicle; determining a TTS rendering process type to be used for the text content from a plurality of TTS rendering process types supported by the networked system, wherein the plurality of TTS rendering process types include: a local TTS rendering process using a local TTS engine at the telematics-equipped vehicle, a remote TTS rendering process with delayed playback using the remote TTS engine, and a remote TTS rendering process with streaming playback using the remote TTS engine; and causing the text content to be rendered as an audio signal for playback by the telematics-equipped vehicle using the determined TTS rendering process type; wherein the determining is based on a quality of service (QoS) level corresponding to a location of the vehicle and a future expected location of the vehicle, and wherein during the determining, the TTS rendering process type is specified as: the local TTS rendering process for a current location corresponding to a first range of QoS levels, the remote TTS rendering process with delayed playback for a current location corresponding to a second range of QoS levels and for an expected transition from a current location corresponding to a third range of QoS levels to a future expected location corresponding to the first or second range of QoS levels; the remote TTS rendering process with streaming playback for a current location corresponding to the third range of QoS levels where there is not an to an expected transition to a future expected location corresponding to the first or second range of QoS levels. | 7. A non-transitory computer-readable medium having processor-executable instructions stored thereon for providing text-to-speech (TTS) functionality to a telematics unit of a telematics-equipped vehicle in a networked system, the processor-executable instructions, when executed by a processor of the telematics unit or a remote TTS engine on a remote server, facilitating performance of the following steps: receiving text content to be played back by an audio system of the telematics-equipped vehicle; determining a TTS rendering process type to be used for the text content from a plurality of TTS rendering process types supported by the networked system, wherein the plurality of TTS rendering process types include: a local TTS rendering process using a local TTS engine at the telematics-equipped vehicle, a remote TTS rendering process with delayed playback using the remote TTS engine, and a remote TTS rendering process with streaming playback using the remote TTS engine; and causing the text content to be rendered as an audio signal for playback by the telematics-equipped vehicle using the determined TTS rendering process type; wherein the determining is based on a quality of service (QoS) level corresponding to a location of the vehicle and a future expected location of the vehicle, and wherein during the determining, the TTS rendering process type is specified as: the local TTS rendering process for a current location corresponding to a first range of QoS levels, the remote TTS rendering process with delayed playback for a current location corresponding to a second range of QoS levels and for an expected transition from a current location corresponding to a third range of QoS levels to a future expected location corresponding to the first or second range of QoS levels; the remote TTS rendering process with streaming playback for a current location corresponding to the third range of QoS levels where there is not an to an expected transition to a future expected location corresponding to the first or second range of QoS levels. 11. The non-transitory computer-readable medium according to claim 7 , wherein the remote TTS rendering process with delayed playback comprises determining an amount of content to buffer prior to playback. | 0.701166 |
9,881,055 | 1 | 3 | 1. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes: converting a SQL expression into an S-expression tabular structure, wherein said S-expression comprises a nested list; generating a function table based on said S-expression tabular structure, wherein said function table comprises a plurality of functions associated with said S expression tabular structure tabulated against at least one of a function name, a derived column and a derived table; generating an argument table based on said S-expression tabular structure, wherein said argument table comprises a plurality of arguments associated with said S expression tabular structure tabulated against at least one of an argument type, a function identification, a computed from function, a reference to entity or a literal value; and converting at least one function associated with said S-expression tabular structure to a pre-determined language, based on a language map of said pre-determined language and said function table and said argument table. | 1. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes: converting a SQL expression into an S-expression tabular structure, wherein said S-expression comprises a nested list; generating a function table based on said S-expression tabular structure, wherein said function table comprises a plurality of functions associated with said S expression tabular structure tabulated against at least one of a function name, a derived column and a derived table; generating an argument table based on said S-expression tabular structure, wherein said argument table comprises a plurality of arguments associated with said S expression tabular structure tabulated against at least one of an argument type, a function identification, a computed from function, a reference to entity or a literal value; and converting at least one function associated with said S-expression tabular structure to a pre-determined language, based on a language map of said pre-determined language and said function table and said argument table. 3. The one or more non-transitory computer readable storage mediums of claim 1 , wherein said reconstructing comprises: a) selecting a function name of said at least one function from said function table and selecting at least one of an argument type, a reference to entity, a literal value, a computed from function for said at least one function from said argument table; b) augmenting an S-expression string for said at least one function with said argument type comprising at least one of a base column, a derived column, a base table, or a derived table along with said reference to entity; c) augmenting said S-expression string for said at least one function with said argument type comprising a literal value; and d) recursively performing steps a) to d) for said argument type comprising a computed function. | 0.736961 |
8,484,730 | 1 | 3 | 1. A computer-implemented method for reporting online behavior, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying a user account subject to parental monitoring; identifying a plurality of online resources accessed by the user account over a period of time; maintaining a reputation database by collecting, aggregating, and analyzing information about each of the plurality of online resources from user devices within a community; determining a reputation for each of the plurality of online resources, wherein: the reputation indicates a level of security threat; determining the reputation comprises providing information identifying each online resource to an online resource reputation system that maintains reputation information for online resources and receiving, from the online resource reputation system, a reputation score for each online resource; generating an online behavior score for the user account based on the reputation score for each online resource in the plurality of online resources, the online behavior score indicating an overall level of security threat posed by online activity on the user account; reporting the online behavior score to a predetermined contact associated with the user account. | 1. A computer-implemented method for reporting online behavior, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying a user account subject to parental monitoring; identifying a plurality of online resources accessed by the user account over a period of time; maintaining a reputation database by collecting, aggregating, and analyzing information about each of the plurality of online resources from user devices within a community; determining a reputation for each of the plurality of online resources, wherein: the reputation indicates a level of security threat; determining the reputation comprises providing information identifying each online resource to an online resource reputation system that maintains reputation information for online resources and receiving, from the online resource reputation system, a reputation score for each online resource; generating an online behavior score for the user account based on the reputation score for each online resource in the plurality of online resources, the online behavior score indicating an overall level of security threat posed by online activity on the user account; reporting the online behavior score to a predetermined contact associated with the user account. 3. The method according to claim 1 , wherein generating the online behavior score for the user account based on the reputation score for each online resource in the plurality of online resources comprises: identifying a reputation threshold; determining whether any reputation included within the reputations for each of the plurality of online resources achieves the reputation threshold. | 0.713549 |
7,987,454 | 6 | 10 | 6. A data processing system for executing a method to emulate at run time the processing of server pages, the system comprising: a processor coupled to memory elements; a library of custom tags; a server page emulator; said server page emulator for reading a server page, including identifying any calls to said library of custom tags; said server page emulator further for emulating any calls to said custom tags identified in said server page, wherein said server page is generated and processed dynamically at runtime; a tag language definition (TLD) file; said server page emulator further for discovering and parsing the tag language definition (TLD) file for this server context; said server page emulator further for parsing said server page to create a tree of nodes for each element of said tree; said server page emulator further for creating and initializing a page context object; said server page emulator further for sequentially processing said tree to identify each said node as one of template text, custom tag start, custom tag end, and expression language (EL) expression; said server page emulator further, responsive to this node being template text, for writing said text directly to final markup; said server page emulator further, responsive to this node being a custom tag start, for processing a custom tag start method including: verifying correctness of attributes, including whether required attributes exist; verifying tag body is empty if required to be so by said TLD file; setting properties of a tag handler instance to include said page context, any parent tag, and any attribute values determined from evaluating any EL expressions; pushing information about this custom tag onto a tag state stack; receiving from said custom tag start method a response code, said response code being one of skip body, evaluate body include, and evaluate body buffered; responsive to said response code being skip body, skipping body; responsive to said response code being one of evaluate body include and evaluate body buffered, invoking methods for page context push body, body tag set body content, and body tag do initiate body; said server page emulator further, responsive to this node being a tag end, for processing a custom tag end method including: determining if this custom tag is an iteration and that said body has been processed, and if not invoking a do end tag method; responsive to this custom tag not being an iteration with said body processed, invoking a do after body method to process each remaining iteration and thereafter invoking said do end tag method; responsive to a skip page response from said do end tag method, arranging for remainder of this page to be skipped; and said server page emulator further, responsive to this node being an EL expression, for evaluating said EL expression and writing result to said final markup. | 6. A data processing system for executing a method to emulate at run time the processing of server pages, the system comprising: a processor coupled to memory elements; a library of custom tags; a server page emulator; said server page emulator for reading a server page, including identifying any calls to said library of custom tags; said server page emulator further for emulating any calls to said custom tags identified in said server page, wherein said server page is generated and processed dynamically at runtime; a tag language definition (TLD) file; said server page emulator further for discovering and parsing the tag language definition (TLD) file for this server context; said server page emulator further for parsing said server page to create a tree of nodes for each element of said tree; said server page emulator further for creating and initializing a page context object; said server page emulator further for sequentially processing said tree to identify each said node as one of template text, custom tag start, custom tag end, and expression language (EL) expression; said server page emulator further, responsive to this node being template text, for writing said text directly to final markup; said server page emulator further, responsive to this node being a custom tag start, for processing a custom tag start method including: verifying correctness of attributes, including whether required attributes exist; verifying tag body is empty if required to be so by said TLD file; setting properties of a tag handler instance to include said page context, any parent tag, and any attribute values determined from evaluating any EL expressions; pushing information about this custom tag onto a tag state stack; receiving from said custom tag start method a response code, said response code being one of skip body, evaluate body include, and evaluate body buffered; responsive to said response code being skip body, skipping body; responsive to said response code being one of evaluate body include and evaluate body buffered, invoking methods for page context push body, body tag set body content, and body tag do initiate body; said server page emulator further, responsive to this node being a tag end, for processing a custom tag end method including: determining if this custom tag is an iteration and that said body has been processed, and if not invoking a do end tag method; responsive to this custom tag not being an iteration with said body processed, invoking a do after body method to process each remaining iteration and thereafter invoking said do end tag method; responsive to a skip page response from said do end tag method, arranging for remainder of this page to be skipped; and said server page emulator further, responsive to this node being an EL expression, for evaluating said EL expression and writing result to said final markup. 10. The system of claim 6 , said server page being a Java server page (JSP), and further comprising: said server page emulator further, while parsing said server page, for writing any text determined to be template text directly to final markup. | 0.733696 |
9,665,622 | 14 | 15 | 14. A method comprising: performing a matching of an input keyword to one or more inquiry words in a search click log; in response to determining that the input keyword does not match any inquiry word in the search click log, rewriting the input keyword; performing a matching of the rewritten keyword to a plurality of inquiry words in the search click log; and in response to determining that the rewritten keyword does not match any inquiry word in the search click log, classifying the input keyword into one or more characteristics, calculating a probability of each characteristic of the one or more characteristics under each category in the search click log, and determining at least one category which probability is higher than a preset threshold as a category that matches the input keyword. | 14. A method comprising: performing a matching of an input keyword to one or more inquiry words in a search click log; in response to determining that the input keyword does not match any inquiry word in the search click log, rewriting the input keyword; performing a matching of the rewritten keyword to a plurality of inquiry words in the search click log; and in response to determining that the rewritten keyword does not match any inquiry word in the search click log, classifying the input keyword into one or more characteristics, calculating a probability of each characteristic of the one or more characteristics under each category in the search click log, and determining at least one category which probability is higher than a preset threshold as a category that matches the input keyword. 15. A method as recited in claim 14 , wherein rewriting the input keyword comprises: labeling a respective importance value for each word included in the input keyword; and deleting a word which respective importance value is lower than a preset importance value threshold. | 0.872311 |
9,836,452 | 1 | 8 | 1. A system comprising: at least one processor; and memory encoding computer executable instructions that, when executed by at least one processor, perform a method for discriminating ambiguous requests comprising: receiving a natural language expression, wherein the natural language expression includes at least one of words, terms, and phrases of text; creating a dialog hypothesis set from the natural language expression by using contextual information, wherein the dialog hypothesis set has a first dialog hypothesis corresponding to a first domain and a second dialog hypothesis corresponding to a second domain; generating, from a first domain engine component and a second domain engine component, a plurality of dialog responses for the dialog hypothesis set; ranking by machine learning techniques the first domain engine component and the second domain engine component based on an analysis of the plurality of the dialog responses; and performing an action with the highest ranked domain engine component. | 1. A system comprising: at least one processor; and memory encoding computer executable instructions that, when executed by at least one processor, perform a method for discriminating ambiguous requests comprising: receiving a natural language expression, wherein the natural language expression includes at least one of words, terms, and phrases of text; creating a dialog hypothesis set from the natural language expression by using contextual information, wherein the dialog hypothesis set has a first dialog hypothesis corresponding to a first domain and a second dialog hypothesis corresponding to a second domain; generating, from a first domain engine component and a second domain engine component, a plurality of dialog responses for the dialog hypothesis set; ranking by machine learning techniques the first domain engine component and the second domain engine component based on an analysis of the plurality of the dialog responses; and performing an action with the highest ranked domain engine component. 8. The system of claim 1 , wherein the ranking further comprises: extracting features from the at least two dialog hypotheses in the dialog hypothesis set; and calculating a score for the extracted features, wherein the calculated score is indicative of the dialog hypothesis rank within the dialog hypothesis set. | 0.600509 |
9,563,646 | 8 | 12 | 8. A system comprising: one or more processors; and one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause performance of operations comprising: providing a database of images and a textual description of the contents of a given image; receiving a search query from a user for retrieving an image associated with a subject matter of interest to the user from the database; evaluating the database including comparing the search query the textual description of the contents of a given image including automatically providing a plurality of images from the database to the user based on the query; receiving a selection of one of the plurality of images from the user; creating an association between the selected image and a concept including storing the association, wherein the concept is related to the subject matter of interest; after creating the association, receiving a request from another user for creating an image advertisement; determining that the request is related to the concept; suggesting the selected image for the image advertisement using the stored association and based at least in part on determining that the request is related to the concept; creating the image advertisement using the selected image; and storing the created image advertisement including storing the created image advertisement in association with the concept. | 8. A system comprising: one or more processors; and one or more computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause performance of operations comprising: providing a database of images and a textual description of the contents of a given image; receiving a search query from a user for retrieving an image associated with a subject matter of interest to the user from the database; evaluating the database including comparing the search query the textual description of the contents of a given image including automatically providing a plurality of images from the database to the user based on the query; receiving a selection of one of the plurality of images from the user; creating an association between the selected image and a concept including storing the association, wherein the concept is related to the subject matter of interest; after creating the association, receiving a request from another user for creating an image advertisement; determining that the request is related to the concept; suggesting the selected image for the image advertisement using the stored association and based at least in part on determining that the request is related to the concept; creating the image advertisement using the selected image; and storing the created image advertisement including storing the created image advertisement in association with the concept. 12. The system of claim 8 , wherein a first image among the plurality of images comprises an animated image. | 0.847458 |
8,347,405 | 8 | 13 | 8. A computer-readable storage device with executable program code stored thereon, the program code for Asynchronous Java Script and XML (AJAX) form-based authentication using Java 2 Platform Enterprise Edition, wherein the program code is executable to perform: issuing, by an AJAX-enabled application on a client, an AJAX request to a server for secure data, the server configured to detect whether an AJAX request sent from a client requires access to data marked as secure and to redirect the AJAX request to an authentication required servlet in response to detecting that the AJAX request requires access to data marked as secure; receiving an AJAX response from the server, the AJAX response, independently of a server-side security credential form, directing the AJAX-enabled application on the client to obtain user security credentials; simulating a form-based submission by prompting a user for the user security credentials independent of a server-based security credential form; and calling a client-side Java application to send the user security credentials by way of a AJAX form-based authentication request to the server in response to receiving the user-entered security credentials, the server configured to authenticate the user security credentials using a web container authentication service and process the client request for secure data in response to a positive authentication of the user security credentials. | 8. A computer-readable storage device with executable program code stored thereon, the program code for Asynchronous Java Script and XML (AJAX) form-based authentication using Java 2 Platform Enterprise Edition, wherein the program code is executable to perform: issuing, by an AJAX-enabled application on a client, an AJAX request to a server for secure data, the server configured to detect whether an AJAX request sent from a client requires access to data marked as secure and to redirect the AJAX request to an authentication required servlet in response to detecting that the AJAX request requires access to data marked as secure; receiving an AJAX response from the server, the AJAX response, independently of a server-side security credential form, directing the AJAX-enabled application on the client to obtain user security credentials; simulating a form-based submission by prompting a user for the user security credentials independent of a server-based security credential form; and calling a client-side Java application to send the user security credentials by way of a AJAX form-based authentication request to the server in response to receiving the user-entered security credentials, the server configured to authenticate the user security credentials using a web container authentication service and process the client request for secure data in response to a positive authentication of the user security credentials. 13. The computer-readable storage device of claim 8 , wherein the server is configured to pass the authentication result to an authentication failed servlet in response to a rejection of the user security credentials, and the authentication failed servlet returns a Java Script Object Notation (JSON) object configured to indicate that authentication has failed. | 0.699336 |
8,909,545 | 2 | 3 | 2. The method of claim 1 , wherein the advertisement is identified based at least in part on a location of the second remote device. | 2. The method of claim 1 , wherein the advertisement is identified based at least in part on a location of the second remote device. 3. The method of claim 2 , further comprising replacing a first word included in the advertisement with a second word, wherein the second word is more effective for marketing purposes than the first word at the location. | 0.915966 |
4,204,090 | 1 | 7 | 1. A process for reducing the redundancy of binary character sequences which describe information including characters and graphic patterns represented in punctiform fashion, wherein within the binary character sequences each binary character having a first binary value is assigned to a point which is to be represented and at least one interval corresponding to one printing element is provided between two points represented by the same output component, wherein each element is divided into a plurality of sub-elements, and wherein the binary character sequences represent the information divided into sub-elements, the improvement therein comprising the steps of: generating and assigning code words such that of the possible combinations of a group of binary characters of the binary code sequences the code words are assigned to those combinations in which a binary character having a first binary value is followed by at least one predetermined number of binary characters having a second binary value, the predetermined number being dependent on the number of sub-elements within a printing element; transmitting the code words, in place of the binary character sequences, to a receiver; receiving the transmitted code words; reassigning the original binary character sequences to the received code words; and feeding the binary character sequences to operate output components. | 1. A process for reducing the redundancy of binary character sequences which describe information including characters and graphic patterns represented in punctiform fashion, wherein within the binary character sequences each binary character having a first binary value is assigned to a point which is to be represented and at least one interval corresponding to one printing element is provided between two points represented by the same output component, wherein each element is divided into a plurality of sub-elements, and wherein the binary character sequences represent the information divided into sub-elements, the improvement therein comprising the steps of: generating and assigning code words such that of the possible combinations of a group of binary characters of the binary code sequences the code words are assigned to those combinations in which a binary character having a first binary value is followed by at least one predetermined number of binary characters having a second binary value, the predetermined number being dependent on the number of sub-elements within a printing element; transmitting the code words, in place of the binary character sequences, to a receiver; receiving the transmitted code words; reassigning the original binary character sequences to the received code words; and feeding the binary character sequences to operate output components. 7. The improved process of claim 1, wherein the step of generating is further defined as: generating the information from alphanumeric characters and symbols. | 0.843254 |
9,646,056 | 8 | 9 | 8. A computer-implemented method for rank-ordering and cognitive saliency schema-based selection, comprising: an act of causing a data processor to execute instructions stored on a non-transitory memory such that upon execution, one or more processors perform operations of: receiving a set of unnormalized probabilities corresponding to a set of objects competing for attentional selection in a current environment, wherein each unnormalized probability in the set of unnormalized probabilities is based on a likelihood estimation of encountering the corresponding object in the current environment; ranking the set of objects based on a set of cognitive saliency values corresponding to the set of objects to generate a rank-ordered list of cognitive saliency values, wherein the set of cognitive saliency values is proportional to the set of unnormalized probabilities; analyzing the rank-ordered list of cognitive saliency values to detect a schema of the current environment by which the set of objects is ranked; learning and storing the schema along with a reward measure of the schema's utility; and selecting a maximum saliency object in the set of objects based on the rank-ordered list of cognitive saliency values. | 8. A computer-implemented method for rank-ordering and cognitive saliency schema-based selection, comprising: an act of causing a data processor to execute instructions stored on a non-transitory memory such that upon execution, one or more processors perform operations of: receiving a set of unnormalized probabilities corresponding to a set of objects competing for attentional selection in a current environment, wherein each unnormalized probability in the set of unnormalized probabilities is based on a likelihood estimation of encountering the corresponding object in the current environment; ranking the set of objects based on a set of cognitive saliency values corresponding to the set of objects to generate a rank-ordered list of cognitive saliency values, wherein the set of cognitive saliency values is proportional to the set of unnormalized probabilities; analyzing the rank-ordered list of cognitive saliency values to detect a schema of the current environment by which the set of objects is ranked; learning and storing the schema along with a reward measure of the schema's utility; and selecting a maximum saliency object in the set of objects based on the rank-ordered list of cognitive saliency values. 9. The method as set forth in claim 8 , wherein the one or more processors perform operations of: recalling the stored schema and the reward measure when presented with a new environment; and appending a set of processing strategies onto the rank-ordered list of cognitive saliency values based on the recall of the stored schema and the reward measure, thereby generating a processed rank-ordered list of cognitive saliency values. | 0.590909 |
10,147,424 | 8 | 14 | 8. A non-transitory computer-readable storage medium containing instructions that, when executed by one or more processors, perform an operation for selecting a response to an audio stream query, the operation comprising: receiving, over a network, a self-support query including spoken content from a user recorded by a remote mobile device; determining a set of paralinguistic features from the spoken content; estimating an emotional state of the user based on the set of paralinguistic features; identifying text strings representing subject matter based on the spoken content in the audio stream query; determining two or more query responses corresponding to the text strings representing the subject matter; selecting, from a query response database, one of the query responses to present to the user based, at least in part, on the emotional state of the user and an uplift model used to select query responses for users with the emotional state; receiving, over the network from the remote mobile device, a user reaction to the query response; determining a favorability metric associated with the user reaction; updating the uplift model based on the attribute of the user, the user reaction and the favorability metric; and based on updating the uplift model, transmitting an additional query response to the remote mobile device, wherein the additional query response is selected based on the uplift model for users with the emotional state of the user. | 8. A non-transitory computer-readable storage medium containing instructions that, when executed by one or more processors, perform an operation for selecting a response to an audio stream query, the operation comprising: receiving, over a network, a self-support query including spoken content from a user recorded by a remote mobile device; determining a set of paralinguistic features from the spoken content; estimating an emotional state of the user based on the set of paralinguistic features; identifying text strings representing subject matter based on the spoken content in the audio stream query; determining two or more query responses corresponding to the text strings representing the subject matter; selecting, from a query response database, one of the query responses to present to the user based, at least in part, on the emotional state of the user and an uplift model used to select query responses for users with the emotional state; receiving, over the network from the remote mobile device, a user reaction to the query response; determining a favorability metric associated with the user reaction; updating the uplift model based on the attribute of the user, the user reaction and the favorability metric; and based on updating the uplift model, transmitting an additional query response to the remote mobile device, wherein the additional query response is selected based on the uplift model for users with the emotional state of the user. 14. The computer-readable storage medium of claim 8 , wherein identifying subject matter corresponding to the spoken content in the audio stream query comprises comparing the spoken content to types of subject matter in a database. | 0.662281 |
7,861,161 | 14 | 15 | 14. A processor-readable medium comprising code for execution by a processor to create a report to be executed on a reporting system, the medium comprising: code for causing a processor to enable a user to select a template with one or more template properties; code for causing a processor to enable a user to select a filter with one or more filter properties; and code for causing a processor to enable a user to specify one or more of the template or filter properties with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report such that the prompt object may be used more than once in a single report or may be used in more than one report. | 14. A processor-readable medium comprising code for execution by a processor to create a report to be executed on a reporting system, the medium comprising: code for causing a processor to enable a user to select a template with one or more template properties; code for causing a processor to enable a user to select a filter with one or more filter properties; and code for causing a processor to enable a user to specify one or more of the template or filter properties with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report such that the prompt object may be used more than once in a single report or may be used in more than one report. 15. The medium of claim 14 wherein at least one validation property comprises verification that the answer provided to the question is of the specified prompt type. | 0.75 |
8,875,038 | 23 | 24 | 23. The method according to claim 14 , wherein the first and the second content areas display content of different first and second content categories, respectively, and wherein: if the indication is of dropping the element into the first content area, the second content items are of the first content category of the first content area, and if the indication is of dropping the element into the second content area, the third content items are of the second content category of the second content area. | 23. The method according to claim 14 , wherein the first and the second content areas display content of different first and second content categories, respectively, and wherein: if the indication is of dropping the element into the first content area, the second content items are of the first content category of the first content area, and if the indication is of dropping the element into the second content area, the third content items are of the second content category of the second content area. 24. The method according to claim 23 , wherein the method further comprises, before receiving the indication of dragging and dropping, displaying, by the web browser, (a) in the first and the second content areas, respective content items requested from respective one or more online content sources, and (b) respective names of the online content sources in association with the respective first and second content areas. | 0.869431 |
8,892,492 | 4 | 10 | 4. A system for declarative network access control, comprising: an interpreter to transform a plurality of sentences in a declarative network access control language to a plurality of rules, wherein one of the plurality of sentences comprises at least one client, an authentication result, at least one condition, and a consequence; a rules engine to evaluate the rules to produce a plurality of actions for providing access control to at least one network at a point of access; at least one storage device to store instructions for the interpreter, the rules and the rules engine; and at least one processor coupled to the storage device to execute the instructions for the interpreter and the rules engine. | 4. A system for declarative network access control, comprising: an interpreter to transform a plurality of sentences in a declarative network access control language to a plurality of rules, wherein one of the plurality of sentences comprises at least one client, an authentication result, at least one condition, and a consequence; a rules engine to evaluate the rules to produce a plurality of actions for providing access control to at least one network at a point of access; at least one storage device to store instructions for the interpreter, the rules and the rules engine; and at least one processor coupled to the storage device to execute the instructions for the interpreter and the rules engine. 10. The system of claim 4 , wherein at least one of the rules further comprises a location. | 0.831481 |
8,593,501 | 1 | 10 | 1. A method comprising: establishing, by a computer having at least one processor and a memory, a communication session for multiple communication devices, wherein: at least two communication devices of the multiple communication devices participate in the communication session as video communication devices, each video communication device is configured to provide audio and video for the communication session, each video communication device is configured to receive audio and video for the communication session, at least one communication device of the multiple communication devices participates in the communication session as an audio communication device, and each audio communication device is configured to provide and receive audio, but not video, for the communication session; connecting a first video communication device to the communication session; connecting a second video communication device to the communication session; receiving a request to connect an audio communication device to the communication session; connecting the audio communication device to the communication session; receiving encoded speech from the audio communication device; performing speech recognition on the encoded speech to obtain speech-recognized text; comparing the speech-recognized text to one or more names stored in a names database; adjusting the speech-recognized text based at least in part on the comparison to generate output text associated with the speech-recognized text; and providing the output text to at least one of the first and second video communication devices for visual identification of the audio communication device. | 1. A method comprising: establishing, by a computer having at least one processor and a memory, a communication session for multiple communication devices, wherein: at least two communication devices of the multiple communication devices participate in the communication session as video communication devices, each video communication device is configured to provide audio and video for the communication session, each video communication device is configured to receive audio and video for the communication session, at least one communication device of the multiple communication devices participates in the communication session as an audio communication device, and each audio communication device is configured to provide and receive audio, but not video, for the communication session; connecting a first video communication device to the communication session; connecting a second video communication device to the communication session; receiving a request to connect an audio communication device to the communication session; connecting the audio communication device to the communication session; receiving encoded speech from the audio communication device; performing speech recognition on the encoded speech to obtain speech-recognized text; comparing the speech-recognized text to one or more names stored in a names database; adjusting the speech-recognized text based at least in part on the comparison to generate output text associated with the speech-recognized text; and providing the output text to at least one of the first and second video communication devices for visual identification of the audio communication device. 10. The method of claim 1 , further comprising: Signaling the audio communication device to prompt a participant of the communication session to provide permission to store the output text in a computer-readable storage medium accessible by the computer; and storing the output text in the computer-readable storage medium after the communication session has ended only when the participant provides permission to store the output text to the computer. | 0.789179 |
10,146,939 | 19 | 20 | 19. The non-transitory computer-readable medium of claim 15 , wherein the training n-grams include a first plurality of distinct training n-grams and a second plurality of distinct training n-grams. | 19. The non-transitory computer-readable medium of claim 15 , wherein the training n-grams include a first plurality of distinct training n-grams and a second plurality of distinct training n-grams. 20. The non-transitory computer-readable medium of claim 19 , wherein the method further comprises: determining a first plurality of appearance frequencies corresponding to the first plurality of distinct training n-grams; and determining a second plurality of appearance frequencies corresponding to the second plurality of distinct training n-grams; and determining a first anomaly detection score based on the first plurality of appearance frequencies and a second anomaly detection score based on the second plurality of appearance frequencies. | 0.609687 |
9,317,601 | 13 | 16 | 13. A non-transitory computer-readable medium comprising: a code set configured receive by a computer a term; a code set configured determined by the computer an ambiguity score for the term, wherein the ambiguity score is based on a ratio of a probability of the term and at least first, second and third language models of a plurality of language models, and wherein the first language model is based on a medical corpus of documents and the second language model is based on a general news corpus of documents and the third language model is based on a legal corpus of documents, wherein the ambiguity score for the term is determined using the function: S t n = λ 1 log ( P ( t n | M 2 ) ) log ( P ( t n | M 1 ) ) + λ 2 log ( P ( t n | M 3 ) ) log ( P ( t n | M 1 ) ) where S t n the ambiguity score for term t n, λ 1 is a first constant, λ 2 is a second constant, P is a function of probability, M 1 is the first language model, M 2 is the second language odel, and M 3 is a third language model; and a code set configured output by the computer the ambiguity score for the term, wherein the ambiguity score for the term is outputted as ranked list, with each score associated with corresponding terms. | 13. A non-transitory computer-readable medium comprising: a code set configured receive by a computer a term; a code set configured determined by the computer an ambiguity score for the term, wherein the ambiguity score is based on a ratio of a probability of the term and at least first, second and third language models of a plurality of language models, and wherein the first language model is based on a medical corpus of documents and the second language model is based on a general news corpus of documents and the third language model is based on a legal corpus of documents, wherein the ambiguity score for the term is determined using the function: S t n = λ 1 log ( P ( t n | M 2 ) ) log ( P ( t n | M 1 ) ) + λ 2 log ( P ( t n | M 3 ) ) log ( P ( t n | M 1 ) ) where S t n the ambiguity score for term t n, λ 1 is a first constant, λ 2 is a second constant, P is a function of probability, M 1 is the first language model, M 2 is the second language odel, and M 3 is a third language model; and a code set configured output by the computer the ambiguity score for the term, wherein the ambiguity score for the term is outputted as ranked list, with each score associated with corresponding terms. 16. The non-transitory computer-readable medium of claim 13 , wherein first language model is based on the Unified Medical Language System (UMLS). | 0.674107 |
9,235,776 | 1 | 2 | 1. A person detection apparatus that detects a person from an input image captured by a capturing portion through pattern recognition using a recognition model to recognize a person, the apparatus comprising: a storage portion that stores a protector-hold recognition model describing a person who is using a protector against a specific weather and a no-protector recognition model describing a person who is using no protector; a weather determination section that determines a weather condition based on a detection result by a weather detection portion; and a person recognition section that performs pattern recognitions to the input image by using the protector-hold recognition model and the no-protector recognition model, which are stored in the storage portion, applies a ratio of an influence on the protector-hold recognition model and a ratio of an influence on the no-protector recognition model, in accordance with a determination result of a weather condition by the weather determination portion, and outputs, as a recognition result, a weather reflection score that is calculated by reflecting the ratio of the influence on the protector-hold recognition model and the ratio of the influence on the no-protector recognition model, respectively, in a result of performing the pattern recognition using the protector-hold recognition model and a result of performing the pattern recognition using the no-protector recognition model. | 1. A person detection apparatus that detects a person from an input image captured by a capturing portion through pattern recognition using a recognition model to recognize a person, the apparatus comprising: a storage portion that stores a protector-hold recognition model describing a person who is using a protector against a specific weather and a no-protector recognition model describing a person who is using no protector; a weather determination section that determines a weather condition based on a detection result by a weather detection portion; and a person recognition section that performs pattern recognitions to the input image by using the protector-hold recognition model and the no-protector recognition model, which are stored in the storage portion, applies a ratio of an influence on the protector-hold recognition model and a ratio of an influence on the no-protector recognition model, in accordance with a determination result of a weather condition by the weather determination portion, and outputs, as a recognition result, a weather reflection score that is calculated by reflecting the ratio of the influence on the protector-hold recognition model and the ratio of the influence on the no-protector recognition model, respectively, in a result of performing the pattern recognition using the protector-hold recognition model and a result of performing the pattern recognition using the no-protector recognition model. 2. The person detection apparatus according to claim 1 wherein: the weather determination section determines a presence or absence of a specific weather or an intensity of a specific weather; and the person recognition section outputs, as a recognition result, a weather reflection score that is acquired by reflecting an influence, which is depending on the presence or absence of the specific weather or the intensity of the specific weather determined by the weather determination section, in a score of a result of performing the pattern recognition by using the protector-hold recognition model. | 0.500832 |
10,109,278 | 1 | 2 | 1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated. | 1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated. 2. The system of claim 1 , wherein the physical computing device is further configured to provide the content synchronization information to a separate computing device. | 0.678707 |
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