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6,157,905 | 28 | 32 | 28. A method in a computer system for transforming a sequence of source values representing text into a sequence of target values that characterizes the sequence of source values in a manner useful for n-gram analysis techniques, the method comprising the steps of: for each distinct source value occurring in the sequence of source values, identifying a single target value corresponding to the distinct source value, such that target value corresponds to one or more distinct source values and at least one target value corresponds to two or more distinct source values; for each occurrence of the distinct source value in the sequence of source values, writing the target value identified as corresponding to the distinct source value to a position in the sequence of target values corresponding to the position of the occurrence of the distinct source value in the sequence of source values; and subjecting the sequence of target values to an n-gram analysis technique in order to analyze the representation of text constituted by the sequence of source values. | 28. A method in a computer system for transforming a sequence of source values representing text into a sequence of target values that characterizes the sequence of source values in a manner useful for n-gram analysis techniques, the method comprising the steps of: for each distinct source value occurring in the sequence of source values, identifying a single target value corresponding to the distinct source value, such that target value corresponds to one or more distinct source values and at least one target value corresponds to two or more distinct source values; for each occurrence of the distinct source value in the sequence of source values, writing the target value identified as corresponding to the distinct source value to a position in the sequence of target values corresponding to the position of the occurrence of the distinct source value in the sequence of source values; and subjecting the sequence of target values to an n-gram analysis technique in order to analyze the representation of text constituted by the sequence of source values. 32. The method of claim 28, further comprising the step of, in response to the subjecting step, detecting a characteristic of the representation of text constituted by the sequence of source values. | 0.881579 |
8,813,007 | 9 | 11 | 9. A non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform a method to formally verify a circuit design, the method comprising: simplifying a first set of assumptions to obtain a second set of assumptions, wherein the second set of assumptions is logically equivalent to the first set of assumptions, and wherein the first set of assumptions and the second set of assumptions correspond to allowable input assignments for the circuit design; associating a first subset of assumptions with an assertion in a set of assertions, wherein the first subset of assumptions is a subset of the second set of assumptions, and wherein satisfying the assertion corresponds to a desired behavior of circuit design; modifying the first subset of assumptions to obtain a second subset of assumptions which is not logically equivalent to the first subset of assumptions; and proving that the circuit design satisfies the assertion when the second subset of assumptions is satisfied. | 9. A non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform a method to formally verify a circuit design, the method comprising: simplifying a first set of assumptions to obtain a second set of assumptions, wherein the second set of assumptions is logically equivalent to the first set of assumptions, and wherein the first set of assumptions and the second set of assumptions correspond to allowable input assignments for the circuit design; associating a first subset of assumptions with an assertion in a set of assertions, wherein the first subset of assumptions is a subset of the second set of assumptions, and wherein satisfying the assertion corresponds to a desired behavior of circuit design; modifying the first subset of assumptions to obtain a second subset of assumptions which is not logically equivalent to the first subset of assumptions; and proving that the circuit design satisfies the assertion when the second subset of assumptions is satisfied. 11. The non-transitory computer-readable storage medium of claim 9 , wherein the second subset of assumptions is an over-approximation of the first set of assumptions. | 0.848732 |
6,154,736 | 38 | 39 | 38. A method for forming an enhanced version of a belief network for subsequent use in assisting a user, through computer-aided probabilistic inferences, in a decision-making process, the method being implemented in a computer system having a processor and a storage device connected to the processor, wherein the storage device stores computer executable instructions and a data structure, the data structure storing the enhanced version of the belief network, the method comprising the steps, implemented by the processor through execution of the instructions, of: receiving an initial version of the belief network with nodes and arcs indicating relationships between the nodes, each node containing a graph with probabilities; adjusting one of the graphs to improve an ability of the one graph to perform probabilistic inference, the graph indicating a relationship among the nodes of the belief network that is not reflected in the initial version of the belief network; and adjusting the initial version of the belief network to reflect the indicated relationship so as to generate the enhanced version of the belief network. | 38. A method for forming an enhanced version of a belief network for subsequent use in assisting a user, through computer-aided probabilistic inferences, in a decision-making process, the method being implemented in a computer system having a processor and a storage device connected to the processor, wherein the storage device stores computer executable instructions and a data structure, the data structure storing the enhanced version of the belief network, the method comprising the steps, implemented by the processor through execution of the instructions, of: receiving an initial version of the belief network with nodes and arcs indicating relationships between the nodes, each node containing a graph with probabilities; adjusting one of the graphs to improve an ability of the one graph to perform probabilistic inference, the graph indicating a relationship among the nodes of the belief network that is not reflected in the initial version of the belief network; and adjusting the initial version of the belief network to reflect the indicated relationship so as to generate the enhanced version of the belief network. 39. A computer-readable medium having computer executable instructions stored therein, said instructions being executed by a computer, for performing the steps of claim 38. | 0.5 |
10,032,455 | 16 | 17 | 16. An electronic device for use in a distributed speech recognition system comprising the electronic device and a network device remote from the electronic device, the electronic device, comprising: at least one storage device configured to store information associated with input audio spoken by a user of the electronic device; an embedded speech recognizer configured to recognize at least a first portion of input audio comprising speech to produce a local speech recognition result, wherein the recognizing is performed, at least in part, using a command grammar activated by the embedded speech recognizer in response to recognizing a command; and at least one processor programmed to: send to the network device, at least a second portion of input audio received by the electronic device; receive, from the network device, a remote speech recognition result corresponding to the at least a second portion of the input audio; perform a pronunciation alignment of the local speech recognition result and the remote speech recognition result; identify, based on the aligned local and remote speech recognition results, a portion of the remote speech recognition result corresponding to a low-confidence part of the local speech recognition result; and train the embedded speech recognizer based, at least in part, on the remote speech recognition result, wherein training the embedded speech recognizer comprises adding the identified portion of the remote speech recognition result to the command grammar used by the embedded speech recognizer to recognize the at least a portion of the input audio. | 16. An electronic device for use in a distributed speech recognition system comprising the electronic device and a network device remote from the electronic device, the electronic device, comprising: at least one storage device configured to store information associated with input audio spoken by a user of the electronic device; an embedded speech recognizer configured to recognize at least a first portion of input audio comprising speech to produce a local speech recognition result, wherein the recognizing is performed, at least in part, using a command grammar activated by the embedded speech recognizer in response to recognizing a command; and at least one processor programmed to: send to the network device, at least a second portion of input audio received by the electronic device; receive, from the network device, a remote speech recognition result corresponding to the at least a second portion of the input audio; perform a pronunciation alignment of the local speech recognition result and the remote speech recognition result; identify, based on the aligned local and remote speech recognition results, a portion of the remote speech recognition result corresponding to a low-confidence part of the local speech recognition result; and train the embedded speech recognizer based, at least in part, on the remote speech recognition result, wherein training the embedded speech recognizer comprises adding the identified portion of the remote speech recognition result to the command grammar used by the embedded speech recognizer to recognize the at least a portion of the input audio. 17. The electronic device of claim 16 , wherein training the embedded speech recognizer further comprises: updating at least one recognition vocabulary associated with the embedded speech recognizer based, at least in part, on the remote speech recognition result. | 0.658031 |
9,507,874 | 6 | 7 | 6. The computer program product of claim 4 , further comprising: computer-readable program code that validates each element of a document instance against a corresponding node of the second schema parse tree. | 6. The computer program product of claim 4 , further comprising: computer-readable program code that validates each element of a document instance against a corresponding node of the second schema parse tree. 7. The computer program product of claim 6 , wherein the corresponding node of the second schema parse tree comprises syntax that calls the user defined validation rule. | 0.5 |
9,495,413 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving a result set from the database in response to the database query, and electronically communicating at least a portion of the result set to an associated user via at least one of electronic mail and short message service. | 2. The method of claim 1 , further comprising: receiving a result set from the database in response to the database query, and electronically communicating at least a portion of the result set to an associated user via at least one of electronic mail and short message service. 3. The method of claim 2 , further comprising: formatting the received result set for display to the user. | 0.5 |
7,664,641 | 25 | 26 | 25. The system of claim 22 , further comprising at least one call center that includes a plurality of agent workstations. | 25. The system of claim 22 , further comprising at least one call center that includes a plurality of agent workstations. 26. The system of claim 25 , wherein at least one of the agent workstations includes at least a telephone and a computer terminal. | 0.5 |
9,335,987 | 8 | 13 | 8. A computer system for determining a largest common series from one or more sets of ordered statements, the computer system comprising: a hardware processor; and a memory communicatively coupled to the processor, wherein the memory is not a transitory signal per se, wherein the memory is encoded with instructions, and wherein the instructions when executed by the processor include: compiling, in a first Elements Plain Text Table (EPTT), each statement from one or more sets of ordered statements, wherein each statement comprises a portion of plain text computer program code; wherein each EPTT comprises a respective script identifier, a respective script direct reference, a respective step number, and a plain text corresponding to each respective statement; recording, in a first Plain Text Count Table (PTCT) and based on the first EPTT, a respective number of appearances of each respective statement; determining, based on the first PTCT, a statement having a largest number of appearances; compiling, in a second EPTT, each statement following the statement having a largest number of appearances, wherein each statement following the statement having a largest number of appearances comprises a first order sequential statement; wherein each respective first order sequential statement comprises a statement in the first EPTT having a respective step number sequential to and greater than a respective step number of the statement having a largest number of appearances; recording, in a second PTCT, a number of appearances of each first order sequential statement; determining, based on the second PTCT, a first order sequential statement having a largest number of appearances following the statement having a largest number of appearances; and storing each appearance of the statement having a largest number of appearances and the first order sequential statement having a largest number of appearances in a Keywords Reference Links Table (KRLT) as the largest common series; wherein the KRLT comprises a respective potential keyword ID, a respective script, a respective keyword row number, and a respective script step number for each respective appearance. | 8. A computer system for determining a largest common series from one or more sets of ordered statements, the computer system comprising: a hardware processor; and a memory communicatively coupled to the processor, wherein the memory is not a transitory signal per se, wherein the memory is encoded with instructions, and wherein the instructions when executed by the processor include: compiling, in a first Elements Plain Text Table (EPTT), each statement from one or more sets of ordered statements, wherein each statement comprises a portion of plain text computer program code; wherein each EPTT comprises a respective script identifier, a respective script direct reference, a respective step number, and a plain text corresponding to each respective statement; recording, in a first Plain Text Count Table (PTCT) and based on the first EPTT, a respective number of appearances of each respective statement; determining, based on the first PTCT, a statement having a largest number of appearances; compiling, in a second EPTT, each statement following the statement having a largest number of appearances, wherein each statement following the statement having a largest number of appearances comprises a first order sequential statement; wherein each respective first order sequential statement comprises a statement in the first EPTT having a respective step number sequential to and greater than a respective step number of the statement having a largest number of appearances; recording, in a second PTCT, a number of appearances of each first order sequential statement; determining, based on the second PTCT, a first order sequential statement having a largest number of appearances following the statement having a largest number of appearances; and storing each appearance of the statement having a largest number of appearances and the first order sequential statement having a largest number of appearances in a Keywords Reference Links Table (KRLT) as the largest common series; wherein the KRLT comprises a respective potential keyword ID, a respective script, a respective keyword row number, and a respective script step number for each respective appearance. 13. The computer system of claim 8 , wherein the instructions when executed by the processor further include: determining a second order sequential statement having a largest number of appearances based on a third PTCT, wherein a third EPTT catalogs each statement having a respective step number sequential to and greater than a respective step number of the first order sequential statement, wherein the third PTCT records a respective number of appearances of each statement based on the third EPTT; and storing each appearance of the statement having a largest number of appearances, the first order sequential statement having a largest number of appearances, and the second order sequential statement having a largest number of appearances in the KRLT as the largest common series. | 0.5 |
9,063,989 | 14 | 17 | 14. A non-transitory computer readable storage medium and one or more computer programs embedded therein the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to: receive a plurality of messages directed to a particular user; determining a respective conversation for each of the plurality of messages; send to a client system for display a first list of conversations including the respective conversation, as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list configured by the computer system to include only identifiers of senders of messages in the conversation corresponding to the row; enable the particular user to identify one or more conversations in the first list of conversations, and to mark the identified one or more conversations as belonging to a particular category while continuing to display at least a portion of the first list of conversations, which includes the identified one or more conversations; and send to the client system for display a second list of conversations. | 14. A non-transitory computer readable storage medium and one or more computer programs embedded therein the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to: receive a plurality of messages directed to a particular user; determining a respective conversation for each of the plurality of messages; send to a client system for display a first list of conversations including the respective conversation, as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list configured by the computer system to include only identifiers of senders of messages in the conversation corresponding to the row; enable the particular user to identify one or more conversations in the first list of conversations, and to mark the identified one or more conversations as belonging to a particular category while continuing to display at least a portion of the first list of conversations, which includes the identified one or more conversations; and send to the client system for display a second list of conversations. 17. The non-transitory computer readable storage medium of claim 14 , wherein the second list of conversations is produced by executing a corresponding search query. | 0.76361 |
8,594,285 | 1 | 3 | 1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. | 1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. 3. The method of claim 1 , further comprising the step of generating a text file comprising a textual translation of at least one of the first and second constituent voice data before the analyzing step, the analyzing step being performed on the text file. | 0.852535 |
9,444,939 | 7 | 9 | 7. An apparatus comprising: a memory to store instructions; and at least one processor to execute the instructions to: receive, during a communication between a first person and a second person, a first plurality of voice signals from the first person and a second plurality of voice signals from the second person; temporarily store, based on intercepting the communication and in a first storage, at least a portion of the first plurality of voice signals and at least a portion of the second plurality of voice signals; detect, based on the first plurality of voice signals and the second plurality of voice signals, portions of utterances included in the first plurality of voice signals or the second plurality of voice signals; combine the portions of utterances to generate multiple utterances; determine, based on the multiple utterances, that particular utterances, of the multiple utterances, include significances, the significances of the particular utterances corresponding to indications of why the particular utterances are important in a given context, and providing information about a subsequent decision concerning how to respond, and the at least one processor, when determining that the particular utterances include significances, is to: analyze information that associates a plurality of utterances with a corresponding significance; and determine, based on analyzing the information, that each of the particular utterances matches an utterance of the plurality of utterances; determine, based on the significances of the particular utterances, if a responsive action is appropriate, the responsive action being based on a nature of the communication, based on types of the particular utterances, and corresponding to a particular action to carry out, the responsive action being appropriate when a threshold number of the particular utterances is satisfied; remove, automatically and without user input, when the responsive action is not appropriate and prior to termination of the communication, the at least the portion of the first plurality of voice signals and the at least the portion of the second plurality of voice signals from the first storage; move, automatically and without the user input, when the responsive action is appropriate and prior to the termination of the communication, the at least the portion of the first plurality of voice signals and the at least the portion of the second plurality of voice signals from the first storage to a second storage, the second storage being different than the first storage; and process, when the responsive action is appropriate, the communication, the at least one processor, when processing the communication, is to deploy the responsive action, prior to the termination of the communication, by: displaying an indication of the responsive action to the second person, where the indication directs the second person to request that a third party monitor the communication substantially in real time, and redirecting the communication to the third party. | 7. An apparatus comprising: a memory to store instructions; and at least one processor to execute the instructions to: receive, during a communication between a first person and a second person, a first plurality of voice signals from the first person and a second plurality of voice signals from the second person; temporarily store, based on intercepting the communication and in a first storage, at least a portion of the first plurality of voice signals and at least a portion of the second plurality of voice signals; detect, based on the first plurality of voice signals and the second plurality of voice signals, portions of utterances included in the first plurality of voice signals or the second plurality of voice signals; combine the portions of utterances to generate multiple utterances; determine, based on the multiple utterances, that particular utterances, of the multiple utterances, include significances, the significances of the particular utterances corresponding to indications of why the particular utterances are important in a given context, and providing information about a subsequent decision concerning how to respond, and the at least one processor, when determining that the particular utterances include significances, is to: analyze information that associates a plurality of utterances with a corresponding significance; and determine, based on analyzing the information, that each of the particular utterances matches an utterance of the plurality of utterances; determine, based on the significances of the particular utterances, if a responsive action is appropriate, the responsive action being based on a nature of the communication, based on types of the particular utterances, and corresponding to a particular action to carry out, the responsive action being appropriate when a threshold number of the particular utterances is satisfied; remove, automatically and without user input, when the responsive action is not appropriate and prior to termination of the communication, the at least the portion of the first plurality of voice signals and the at least the portion of the second plurality of voice signals from the first storage; move, automatically and without the user input, when the responsive action is appropriate and prior to the termination of the communication, the at least the portion of the first plurality of voice signals and the at least the portion of the second plurality of voice signals from the first storage to a second storage, the second storage being different than the first storage; and process, when the responsive action is appropriate, the communication, the at least one processor, when processing the communication, is to deploy the responsive action, prior to the termination of the communication, by: displaying an indication of the responsive action to the second person, where the indication directs the second person to request that a third party monitor the communication substantially in real time, and redirecting the communication to the third party. 9. The apparatus of claim 7 , where the responsive action is deployed by displaying an indication to modify at least one response of the second person to the first person. | 0.793976 |
9,928,840 | 15 | 17 | 15. A computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a hotword detector of a mobile computing device that includes (a) the hotword detector, (b) an ultrasonic audio subsystem, and (c) a replay attack engine and that is (i) operating in a mode in which access to one or more resources is disabled, and (ii) configured to exit the mode in which access to the one or more resources is disabled upon detecting an utterance of a hotword, an initial audio input corresponding to an utterance of an initial portion of a hotword; while a remaining portion of the hotword is being uttered and before the hotword is fully uttered, providing, by the ultrasonic audio subsystem of the mobile computing device, verification audio for output through a speaker of the mobile computing device; and selectively exiting, by the replay attack engine of the mobile computing device, the mode in which access to the one or more resources is disabled after the hotword is fully uttered. | 15. A computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a hotword detector of a mobile computing device that includes (a) the hotword detector, (b) an ultrasonic audio subsystem, and (c) a replay attack engine and that is (i) operating in a mode in which access to one or more resources is disabled, and (ii) configured to exit the mode in which access to the one or more resources is disabled upon detecting an utterance of a hotword, an initial audio input corresponding to an utterance of an initial portion of a hotword; while a remaining portion of the hotword is being uttered and before the hotword is fully uttered, providing, by the ultrasonic audio subsystem of the mobile computing device, verification audio for output through a speaker of the mobile computing device; and selectively exiting, by the replay attack engine of the mobile computing device, the mode in which access to the one or more resources is disabled after the hotword is fully uttered. 17. The computer-readable storage device of claim 15 , wherein the hotword is a particular term that triggers semantic interpretation of an additional term of one or more terms that follow the particular term. | 0.869538 |
7,665,063 | 22 | 23 | 22. The method of claim 20 , wherein said dependency network comprises a DAG dependency network. | 22. The method of claim 20 , wherein said dependency network comprises a DAG dependency network. 23. The method of claim 22 , wherein said step of updating values of other variables participating in said declarative rule comprises performing a forward search of said DAG dependency network. | 0.5 |
9,236,049 | 5 | 6 | 5. The mash-up service generation apparatus of claim 3 , wherein the runtime manager drives the runtime code to generate a mash-up service. | 5. The mash-up service generation apparatus of claim 3 , wherein the runtime manager drives the runtime code to generate a mash-up service. 6. The mash-up service generation apparatus of claim 5 , further comprising a mash-up display configured to display the mash-up service on a web browser. | 0.5 |
8,941,589 | 138 | 139 | 138. The system of claim 130 , wherein controlling the component comprises controlling a three-space object in six degrees of freedom simultaneously by mapping the gesture to the three-space object, wherein the plurality of objects includes the three-space object. | 138. The system of claim 130 , wherein controlling the component comprises controlling a three-space object in six degrees of freedom simultaneously by mapping the gesture to the three-space object, wherein the plurality of objects includes the three-space object. 139. The system of claim 138 , wherein the three-space object is presented on a display device coupled to the processor. | 0.748954 |
9,713,774 | 1 | 4 | 1. A computer-implemented method to manage interactions between users of different user classifications in an online environment, the computer-implemented method comprising: determining a first user classification to assign to a first user of a plurality of users in the online environment, by operation of one or more computer processors and based on: (i) an activity type preferred by the first user; (ii) an activity chat frequency exhibited by the first user; and (iii) an activity skill level exhibited by the first user; assigning the first user classification to the first user; monitoring interactions between the plurality of users in the online environment; determining, based on the monitored interactions and at a first point in time, a first set of expressions satisfying a recent usage frequency by users assigned the first user classification, each expression comprising a respective chat message, whereafter only the first set of expressions is conveyed as being selectable by the first user to send to other users of the online environment; responsive to a selection of a first expression of the first set of expressions by the first user, sending the first expression to a specified, second user of the plurality of users without requiring the first user to compose the first expression; and determining, based on the monitored interactions and at a second point in time subsequent to the first point in time, a second set of expressions satisfying the recent usage frequency by users assigned the first user classification, wherein the second set of expressions is distinct from the first set of expressions, whereafter only the second set of expressions is conveyed as being selectable by the second user to send to other users of the online environment; wherein distinct sets of expressions are conveyed to the first user for selection as usage of expressions, by users assigned the first user classification, evolves over time. | 1. A computer-implemented method to manage interactions between users of different user classifications in an online environment, the computer-implemented method comprising: determining a first user classification to assign to a first user of a plurality of users in the online environment, by operation of one or more computer processors and based on: (i) an activity type preferred by the first user; (ii) an activity chat frequency exhibited by the first user; and (iii) an activity skill level exhibited by the first user; assigning the first user classification to the first user; monitoring interactions between the plurality of users in the online environment; determining, based on the monitored interactions and at a first point in time, a first set of expressions satisfying a recent usage frequency by users assigned the first user classification, each expression comprising a respective chat message, whereafter only the first set of expressions is conveyed as being selectable by the first user to send to other users of the online environment; responsive to a selection of a first expression of the first set of expressions by the first user, sending the first expression to a specified, second user of the plurality of users without requiring the first user to compose the first expression; and determining, based on the monitored interactions and at a second point in time subsequent to the first point in time, a second set of expressions satisfying the recent usage frequency by users assigned the first user classification, wherein the second set of expressions is distinct from the first set of expressions, whereafter only the second set of expressions is conveyed as being selectable by the second user to send to other users of the online environment; wherein distinct sets of expressions are conveyed to the first user for selection as usage of expressions, by users assigned the first user classification, evolves over time. 4. The computer-implemented method of claim 1 , wherein the first user classification includes a set of one or more classification criteria, wherein the first user classification is determined to be assigned to the first user by matching monitored interactions with the online environment engaged in by the first user with the set of one or more classification criteria. | 0.598698 |
9,794,766 | 14 | 15 | 14. The computing system of claim 12 , wherein the operation of identifying a plurality of candidate entities based at least in part on the estimated location of the wireless network access point comprises identifying the plurality of candidate entities located within a radius of the estimated location of the wireless network access point. | 14. The computing system of claim 12 , wherein the operation of identifying a plurality of candidate entities based at least in part on the estimated location of the wireless network access point comprises identifying the plurality of candidate entities located within a radius of the estimated location of the wireless network access point. 15. The computing system of claim 14 , wherein the radius is determined as a function of one or more of an uncertainty associated with the estimated location of the wireless network access point, an uncertainty associated with the location of the entity in the database of entity information, and an estimated range of the wireless network access point. | 0.5 |
8,255,219 | 25 | 28 | 25. An apparatus for improving performance of a speech recognition system comprising: a processor that is configured to determine a performance of the speech recognition system based on either recognition of instances of a word or recognition of instances of various words among a set of words; the processor further configured to determine a corrective action based on the previously determined performance to improve the performance of the speech recognition system. | 25. An apparatus for improving performance of a speech recognition system comprising: a processor that is configured to determine a performance of the speech recognition system based on either recognition of instances of a word or recognition of instances of various words among a set of words; the processor further configured to determine a corrective action based on the previously determined performance to improve the performance of the speech recognition system. 28. The apparatus of claim 25 , wherein the apparatus determines the performance and determines the corrective action as the system, is being used by a user. | 0.791223 |
10,019,986 | 1 | 3 | 1. A method comprising: receiving, from a client device and by a voice search system that includes (i) an automated speech recognizer that uses an acoustic model to transcribe utterances, (ii) a search engine, (iii) an acoustic model trainer that periodically retrains the acoustic model using portions of audio data that correspond to manually specified terms of first transcriptions, (iv) a user interface component, and (v) a correction classifier, first audio data corresponding to an utterance of a user; obtaining, by the automated speech recognizer of the voice search system, a first transcription of the first audio data; receiving, by the user interface component of the voice search system, data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms that the user has manually specified as a replacement for the one or more terms; determining, by the correction classifier of the voice search system, a minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms; determining, by the correction classifier of the voice search system and based at least on the minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms that the user has manually specified as a replacement for the one or more terms, whether one or more of the replacement terms that the user has manually specified as a replacement for the one or more terms likely represent a correction of one or more of the one or more terms of the first transcription; in response to determining, based at least on the minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms that the user has manually specified as a replacement for the one or more terms, whether the one or more of the replacement terms that the user has manually specified as a replacement for the one or more terms likely represent a correction of the one or more terms of the first transcription, selectively retraining, by the acoustic model trainer of the voice search system, the acoustic model, comprising (i) retraining the acoustic model of the automated speech recognizer using a first portion of the audio that is associated with the one or more terms of the first transcription when the correction classifier indicates that the replacement terms likely represent a correction, or (ii) bypassing retraining of the acoustic model of the automated speech recognizer using the first portion of the first audio data that is associated with the one or more terms of the first transcription when the correction classifier indicates that the replacement terms do not likely represent a correction; obtaining, by the automated speech recognizer of the voice search system and using the retrained acoustic model, a transcription of audio data corresponding to a subsequently received utterance; and providing, by the user interface component of the voice search system, a user interface that includes one or more search results that the search engine of the voice search system has identified in response to the transcription of the audio data corresponding to the subsequently received utterance. | 1. A method comprising: receiving, from a client device and by a voice search system that includes (i) an automated speech recognizer that uses an acoustic model to transcribe utterances, (ii) a search engine, (iii) an acoustic model trainer that periodically retrains the acoustic model using portions of audio data that correspond to manually specified terms of first transcriptions, (iv) a user interface component, and (v) a correction classifier, first audio data corresponding to an utterance of a user; obtaining, by the automated speech recognizer of the voice search system, a first transcription of the first audio data; receiving, by the user interface component of the voice search system, data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms that the user has manually specified as a replacement for the one or more terms; determining, by the correction classifier of the voice search system, a minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms; determining, by the correction classifier of the voice search system and based at least on the minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms that the user has manually specified as a replacement for the one or more terms, whether one or more of the replacement terms that the user has manually specified as a replacement for the one or more terms likely represent a correction of one or more of the one or more terms of the first transcription; in response to determining, based at least on the minimum edit distance between the one or more terms of the first transcription and the one or more replacement terms that the user has manually specified as a replacement for the one or more terms, whether the one or more of the replacement terms that the user has manually specified as a replacement for the one or more terms likely represent a correction of the one or more terms of the first transcription, selectively retraining, by the acoustic model trainer of the voice search system, the acoustic model, comprising (i) retraining the acoustic model of the automated speech recognizer using a first portion of the audio that is associated with the one or more terms of the first transcription when the correction classifier indicates that the replacement terms likely represent a correction, or (ii) bypassing retraining of the acoustic model of the automated speech recognizer using the first portion of the first audio data that is associated with the one or more terms of the first transcription when the correction classifier indicates that the replacement terms do not likely represent a correction; obtaining, by the automated speech recognizer of the voice search system and using the retrained acoustic model, a transcription of audio data corresponding to a subsequently received utterance; and providing, by the user interface component of the voice search system, a user interface that includes one or more search results that the search engine of the voice search system has identified in response to the transcription of the audio data corresponding to the subsequently received utterance. 3. The method of claim 1 , wherein determining the minimum edit distance comprises determining a phonetic distance between each of the one or more terms of the first transcription and each of the one or more of the replacement terms. | 0.672753 |
9,177,554 | 13 | 17 | 13. A computer program product for reporting sentiment of a product, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by at least one processor of a computer is configured to perform: performing a text analysis on communications; determining at least one feature for the product based on the text analysis; generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength; determining a date associated with each of the sentiment values by extracting the date from the communications; for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules; and reporting how the sentiment values changed over time based on each date. | 13. A computer program product for reporting sentiment of a product, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by at least one processor of a computer is configured to perform: performing a text analysis on communications; determining at least one feature for the product based on the text analysis; generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength; determining a date associated with each of the sentiment values by extracting the date from the communications; for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules; and reporting how the sentiment values changed over time based on each date. 17. The computer program product of claim 13 , wherein each date is selected from: a purchase date; and a communication date. | 0.760536 |
9,092,302 | 15 | 16 | 15. The method of claim 1 , wherein querying the device profile repository comprises weighting device version profile information of at least one device instances according to a source classification. | 15. The method of claim 1 , wherein querying the device profile repository comprises weighting device version profile information of at least one device instances according to a source classification. 16. The method of claim 15 , wherein weighting the device version profile information comprises penalizing consideration of device version profile with a first set of characteristics of tool version information. | 0.5 |
10,013,488 | 17 | 24 | 17. A non-transitory computer-readable storage medium storing instructions which, when executed, cause a processing device to: apply a first predetermined set of rules to an electronic media item to identify a first set of regions, wherein a plurality of regions in the first set of regions is associated with a first region type, the first predetermined set of rules specifying a combination of typographical features used to identify the first region type; analyze one or more regions in the first set of regions to determine a typographical feature set for the one or more regions; perform, by the processing device, a cluster analysis to identify a first cluster of regions from the first set of regions, where a first typographical feature set of a first region in the first cluster and a second typographical feature set of a second region in the first cluster comprise values that are within a threshold of a desired value for the first cluster; update the first predetermined set of rules to account for typographical feature values determined from a centroid of the first cluster of regions to generate a first updated set of rules; and apply the first updated set of rules to the electronic media item to identify one or more regions associated with the first region type. | 17. A non-transitory computer-readable storage medium storing instructions which, when executed, cause a processing device to: apply a first predetermined set of rules to an electronic media item to identify a first set of regions, wherein a plurality of regions in the first set of regions is associated with a first region type, the first predetermined set of rules specifying a combination of typographical features used to identify the first region type; analyze one or more regions in the first set of regions to determine a typographical feature set for the one or more regions; perform, by the processing device, a cluster analysis to identify a first cluster of regions from the first set of regions, where a first typographical feature set of a first region in the first cluster and a second typographical feature set of a second region in the first cluster comprise values that are within a threshold of a desired value for the first cluster; update the first predetermined set of rules to account for typographical feature values determined from a centroid of the first cluster of regions to generate a first updated set of rules; and apply the first updated set of rules to the electronic media item to identify one or more regions associated with the first region type. 24. The non-transitory computer-readable storage medium of claim 17 , wherein the first region type comprises one or more of: a chapter heading, a graphic, a body text, a header, a footer, a table, a list item, a footnote, a table of contents entry, or an equation. | 0.845571 |
4,648,091 | 9 | 10 | 9. A method for decoding a data word from an extended Golay (24,12) code word, said extended Golay code word having been encoded to include said data word, a parity word and an overall parity bit, wherein fewer than a first predetermined number of bits of said first binary message word may have been corrupted after encoding, comprising: (a) cyclicly shifting one bit of a predetermined first linear block code word one bit position, said first linear block code word consisting of one less than the number of bits of said extended Golay code word; (b) logically comparing the first bit of said extended Golay code word with the first bit of a predetermined binary message word; (c) repeating steps a and b for each next respective sequential bit of said extended Golay code word and binary message word, respectively, when comparison of step b determines that the respective bits of said extended Golay code word and binary message word are logically equivalent; (d) logically comparing the immediately preceding bit having been cyclicly shifted with the respective bit of said extended Golay code word when comparison of step b determines that the respective bits of said extended Golay code word and said binary message word are not logically equivalent; (e) decreasing a second predetermined number by one when comparison of step d determines that the immediately preceding bit having been cyclicly shifted is logically equivalent to the respective bit of said extended Golay code word; (f) increasing said second predetermined number by one when comparison of step d determines that the immediately preceding bit having been cyclicly shifted is not logically equivalent to the respective bit of said extended Golay code word; (g) comparing said second predetermined number with said first predetermined number and repeating steps a through f for each next respective sequential bit of said extended Golay code word and said binary message word, respectively, when comparison determines that said second predetermined number is less than said first predetermined number; (h) exclusively ORing the present status of said first linear block code word with the respective sequence of bits of said extended Golay code word having already been compared by execution of step b when comparison of step g determines that said second predetermined number is equal to said first predetermined number; (i) logically ANDing the result of step h with a plurality of a predetermined second linear block code word; (j) comparing the result of step i with the respective one of the plurality of second linear block code words having generated the result of step i; (k) exclusively ORing the present status of said first linear block code word with the respective one of the plurality of second linear block code words having generated an equality for step j; (l) substituting the result of step k for the present status of said first linear block code word; and (m) repeating steps a through l until a predetermined number of bits of said extended Golay code word have been examined. | 9. A method for decoding a data word from an extended Golay (24,12) code word, said extended Golay code word having been encoded to include said data word, a parity word and an overall parity bit, wherein fewer than a first predetermined number of bits of said first binary message word may have been corrupted after encoding, comprising: (a) cyclicly shifting one bit of a predetermined first linear block code word one bit position, said first linear block code word consisting of one less than the number of bits of said extended Golay code word; (b) logically comparing the first bit of said extended Golay code word with the first bit of a predetermined binary message word; (c) repeating steps a and b for each next respective sequential bit of said extended Golay code word and binary message word, respectively, when comparison of step b determines that the respective bits of said extended Golay code word and binary message word are logically equivalent; (d) logically comparing the immediately preceding bit having been cyclicly shifted with the respective bit of said extended Golay code word when comparison of step b determines that the respective bits of said extended Golay code word and said binary message word are not logically equivalent; (e) decreasing a second predetermined number by one when comparison of step d determines that the immediately preceding bit having been cyclicly shifted is logically equivalent to the respective bit of said extended Golay code word; (f) increasing said second predetermined number by one when comparison of step d determines that the immediately preceding bit having been cyclicly shifted is not logically equivalent to the respective bit of said extended Golay code word; (g) comparing said second predetermined number with said first predetermined number and repeating steps a through f for each next respective sequential bit of said extended Golay code word and said binary message word, respectively, when comparison determines that said second predetermined number is less than said first predetermined number; (h) exclusively ORing the present status of said first linear block code word with the respective sequence of bits of said extended Golay code word having already been compared by execution of step b when comparison of step g determines that said second predetermined number is equal to said first predetermined number; (i) logically ANDing the result of step h with a plurality of a predetermined second linear block code word; (j) comparing the result of step i with the respective one of the plurality of second linear block code words having generated the result of step i; (k) exclusively ORing the present status of said first linear block code word with the respective one of the plurality of second linear block code words having generated an equality for step j; (l) substituting the result of step k for the present status of said first linear block code word; and (m) repeating steps a through l until a predetermined number of bits of said extended Golay code word have been examined. 10. The method as in claim 9, wherein said plurality of second linear block code words comprises words including a logical one in the least significant bit position and a total number of logical ones equal to one plus twice said second predetermined number. | 0.608232 |
9,792,588 | 18 | 19 | 18. Anon-transitory machine-readable storage medium including instructions, which, when executed by one or more computer processor of a machine, cause the machine to perform operations, the operations comprising: generating a recommendation graph represented as a matrix listing vertices on both the vertical and horizontal axes and edges as entries corresponding to an intersection of the vertices, each of the vertices representing respective electronic profiles of members of the social networking service, each of the edges representing a recommendation of a recommendee member of the social networking service by a recommender member of the social networking service; training a reputation model to learn a respective importance for each respective feature of a subset of features of the electronic profiles, the training including providing the generated recommendation graph to a classifier; estimating a professional reputation of a member, the estimating including applying the trained reputation model to a feature vector of the member, the feature vector including feature values for the subset of the features, the applying including adjusting at least one of the feature values by a respective weight corresponding to the respective learned importance of the respective feature; aggregating a set of estimated professional reputations of members that have engaged with the content item stored in the database of the online social networking service; performing the identifying based on the aggregated set of estimated professional reputations; and determining a target audience for the content item based on the identifying. | 18. Anon-transitory machine-readable storage medium including instructions, which, when executed by one or more computer processor of a machine, cause the machine to perform operations, the operations comprising: generating a recommendation graph represented as a matrix listing vertices on both the vertical and horizontal axes and edges as entries corresponding to an intersection of the vertices, each of the vertices representing respective electronic profiles of members of the social networking service, each of the edges representing a recommendation of a recommendee member of the social networking service by a recommender member of the social networking service; training a reputation model to learn a respective importance for each respective feature of a subset of features of the electronic profiles, the training including providing the generated recommendation graph to a classifier; estimating a professional reputation of a member, the estimating including applying the trained reputation model to a feature vector of the member, the feature vector including feature values for the subset of the features, the applying including adjusting at least one of the feature values by a respective weight corresponding to the respective learned importance of the respective feature; aggregating a set of estimated professional reputations of members that have engaged with the content item stored in the database of the online social networking service; performing the identifying based on the aggregated set of estimated professional reputations; and determining a target audience for the content item based on the identifying. 19. The non-transitory machine-readable storage medium of claim 18 , wherein at least one of the edges is associated with a label designated by the recommender member and accepted by the recommendee member; wherein the label describes a professional relationship between the recommender member and the recommendee member; and wherein the label is one of “managed recommendee directly”, “reported directly to recommendee”, “managed recommendee indirectly”, “reported indirectly to recommendee”, “senior to recommendee, but not in recommendee's chain of command”, “junior to recommendee, but recommendee not in chain of command”, “worked with recommendee in the same group”, and “worked with recommendee in different groups”. | 0.5 |
7,913,225 | 6 | 7 | 6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. | 6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. 7. The computer program product in accordance with claim 6 , wherein identifying an object in the graphical model that does not conform with one or more rules of a constraint that is imposed on the graphical model comprises listing the object in a task list. | 0.757062 |
9,075,983 | 7 | 8 | 7. A method for authorizing access, comprising the step of: generating for display at least one distorted string of alphanumeric characters, in combination with at least one of a glyph, picture or symbol, the glyph, picture or symbol being foreign to a target audience, the generating step including: generating a random background; separating the at least one distorted string of alphanumeric characters into two or more strings, and adding at least one of the glyph, picture or symbol to one or more ends of the two or more strings to form at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol; and combining the random background with the at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol, using a random template; and comparing a response of a user entered in reaction to the distorted string of alphanumeric characters to a reference string of characters to determine whether to grant access. | 7. A method for authorizing access, comprising the step of: generating for display at least one distorted string of alphanumeric characters, in combination with at least one of a glyph, picture or symbol, the glyph, picture or symbol being foreign to a target audience, the generating step including: generating a random background; separating the at least one distorted string of alphanumeric characters into two or more strings, and adding at least one of the glyph, picture or symbol to one or more ends of the two or more strings to form at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol; and combining the random background with the at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol, using a random template; and comparing a response of a user entered in reaction to the distorted string of alphanumeric characters to a reference string of characters to determine whether to grant access. 8. The method according to claim 7 wherein the at least one string of random alphanumeric characters comprises at least one word. | 0.706818 |
8,965,893 | 19 | 20 | 19. The document clustering system of claim 18 , wherein determining whether the document should be grouped with the one or more previously created cluster summaries comprises: creating a feature vector for the document, the feature vector representing content of the documents; comparing the feature vector with the one or more previously created cluster summaries to identify the cluster summary that is closest to the feature vector and determining a measure of similarities between the cluster summary and the feature vector; determining whether the cluster summary that was identified as the closest to the feature vector is sufficiently close to the feature vector by comparing the measure of the similarities with one or more predetermined thresholds; and if the cluster summary that was identified as the closest to the feature vector is not sufficiently close, then determining that the document should not be grouped with the one or more previously created cluster summaries. | 19. The document clustering system of claim 18 , wherein determining whether the document should be grouped with the one or more previously created cluster summaries comprises: creating a feature vector for the document, the feature vector representing content of the documents; comparing the feature vector with the one or more previously created cluster summaries to identify the cluster summary that is closest to the feature vector and determining a measure of similarities between the cluster summary and the feature vector; determining whether the cluster summary that was identified as the closest to the feature vector is sufficiently close to the feature vector by comparing the measure of the similarities with one or more predetermined thresholds; and if the cluster summary that was identified as the closest to the feature vector is not sufficiently close, then determining that the document should not be grouped with the one or more previously created cluster summaries. 20. The document clustering system of claim 19 , wherein the processor is further configured to: if it is determined that the document should be grouped with the one or more previously created cluster summaries then add the feature vector to the cluster summary that was identified as the closest to the feature vector. | 0.5 |
9,514,219 | 5 | 7 | 5. A system according to claim 4 , further comprising: a further document selection module to select the unclassified documents with similar text when the text is less inclusive of the words in the search string than the text that is the same as the compared portion of the highlighted text in the document. | 5. A system according to claim 4 , further comprising: a further document selection module to select the unclassified documents with similar text when the text is less inclusive of the words in the search string than the text that is the same as the compared portion of the highlighted text in the document. 7. A system according to claim 5 , further comprising: a delivery module to provide the search string to the user for review; and a receipt module to receive from the user, instructions comprising one of exporting the search string, deactivating the search string, and editing the search string. | 0.5 |
9,355,094 | 13 | 15 | 13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving data indicating a movement of a client device by a first user; determining that the movement of the client device is classified as a delimiter motion for; and based on determining that the movement is classified as a delimiter motion, switching between a first mode, in which the client device (i) configures a language setting of an automated speech recognition engine to transcribe the speech of the first user into text that is in the first language, and (ii) provides a first interface that includes the transcribed text of the first user that is in the first language, and a translation of the transcribed text of the first user that is in a second language, and a second mode, in which the client device (i) configures the language setting of the automated speech recognition engine to transcribe the speech of a second user into text that is in the second language, and (ii) provides a second interface that includes the transcribed text of the second user that is in the second language, and a translation of the transcribed text of the second user that is in the first language, wherein the second interface is different from the first interface, and wherein switching between the first mode and the second mode occurs without the second user physically interacting with the client device. | 13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving data indicating a movement of a client device by a first user; determining that the movement of the client device is classified as a delimiter motion for; and based on determining that the movement is classified as a delimiter motion, switching between a first mode, in which the client device (i) configures a language setting of an automated speech recognition engine to transcribe the speech of the first user into text that is in the first language, and (ii) provides a first interface that includes the transcribed text of the first user that is in the first language, and a translation of the transcribed text of the first user that is in a second language, and a second mode, in which the client device (i) configures the language setting of the automated speech recognition engine to transcribe the speech of a second user into text that is in the second language, and (ii) provides a second interface that includes the transcribed text of the second user that is in the second language, and a translation of the transcribed text of the second user that is in the first language, wherein the second interface is different from the first interface, and wherein switching between the first mode and the second mode occurs without the second user physically interacting with the client device. 15. The computer-readable medium of claim 13 , wherein the operations further comprise, while the client device is in the first mode, receiving an utterance of the first user in the first language; and outputting an audio signal encoding the translation of the transcribed text of the first user that is in the second language. | 0.5 |
8,005,680 | 1 | 33 | 1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models. | 1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models. 33. The method according to claim 1 , further comprising the step of using user dependant speech acoustic models delivered by said speech recognition system for personalizing said aspect of said service unrelated to speech processing. | 0.752119 |
8,005,711 | 1 | 5 | 1. A computer implemented method for collecting respondent ratings, comprising: a) presenting a concept to a respondent; b) providing a display surface having a rating scale for a first attribute along a first degree of freedom and a rating scale for a second attribute along a second degree of freedom; c) enabling the respondent to position a representation of the concept at a point on the display surface, the positioned point simultaneously defining ratings on both first and second attribute rating scales; d) using a display deck to present a plurality of concepts in a sequence determined by a researcher, each concept being removed from the deck when positioned on the display surface by the respondent; e) displaying an instruction for positioning concept representations on the display surface; f) enabling the respondent to submit ratings on the plurality of concepts by selecting a button; g) collecting ratings on the plurality of concepts from a plurality of respondents, each respondent being identified by segmentation data; h) enabling the researcher to select respondents by categories of said segmentation data; i) displaying the number of respondents included within the selected segmentation categories; j) enabling the researcher to select a statistical formula for aggregating rating data on the concepts for the selected respondents; and k) displaying each concept at a point on the display surface, the display point being defined by the aggregated ratings on the first and second attribute rating scales, wherein each of said steps a) through k) are performed by the computer. | 1. A computer implemented method for collecting respondent ratings, comprising: a) presenting a concept to a respondent; b) providing a display surface having a rating scale for a first attribute along a first degree of freedom and a rating scale for a second attribute along a second degree of freedom; c) enabling the respondent to position a representation of the concept at a point on the display surface, the positioned point simultaneously defining ratings on both first and second attribute rating scales; d) using a display deck to present a plurality of concepts in a sequence determined by a researcher, each concept being removed from the deck when positioned on the display surface by the respondent; e) displaying an instruction for positioning concept representations on the display surface; f) enabling the respondent to submit ratings on the plurality of concepts by selecting a button; g) collecting ratings on the plurality of concepts from a plurality of respondents, each respondent being identified by segmentation data; h) enabling the researcher to select respondents by categories of said segmentation data; i) displaying the number of respondents included within the selected segmentation categories; j) enabling the researcher to select a statistical formula for aggregating rating data on the concepts for the selected respondents; and k) displaying each concept at a point on the display surface, the display point being defined by the aggregated ratings on the first and second attribute rating scales, wherein each of said steps a) through k) are performed by the computer. 5. The method of claim 1 , wherein the selected statistical formula for aggregating rating data is drawn from the group of: mean, median. | 0.796736 |
8,005,677 | 13 | 14 | 13. The server of claim 11 , wherein: the interface is further operable to cause the text-to-speech server to generate a plurality of model voice samples; and the speaker models are determined based on analysis of the model voice samples. | 13. The server of claim 11 , wherein: the interface is further operable to cause the text-to-speech server to generate a plurality of model voice samples; and the speaker models are determined based on analysis of the model voice samples. 14. The server of claim 13 , wherein the model voice samples are generated based on a text sample associated with the voice sample. | 0.5 |
8,941,870 | 15 | 21 | 15. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: access a selected data source including data to be inserted into a plurality of files generated using a template and a data source; receive user input identifying template elements that act as location placeholders within an electronic document for data from the data source; generate a template from the electronic document using the identified template elements; generate a preview of a file generated using the template and the data source, the preview visible on the display device; receive selection of an output destination for the plurality of files generated using the template and the data source; generate the plurality of files using the template and the data source; and send the plurality of files to the output destination. | 15. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: access a selected data source including data to be inserted into a plurality of files generated using a template and a data source; receive user input identifying template elements that act as location placeholders within an electronic document for data from the data source; generate a template from the electronic document using the identified template elements; generate a preview of a file generated using the template and the data source, the preview visible on the display device; receive selection of an output destination for the plurality of files generated using the template and the data source; generate the plurality of files using the template and the data source; and send the plurality of files to the output destination. 21. The apparatus of claim 15 wherein the instructions will further cause the processor to scan the physical document, the physical document including the template elements, to thereby generate the electronic document. | 0.646104 |
9,489,657 | 6 | 7 | 6. The computer-implemented method of claim 1 in which one of the chat room summaries is designated by a user as an active chat room summary, said active chat room summary including a scrolling full-text display of an ongoing dialog by participants in the chat room, and wherein remaining additional chat room summaries. | 6. The computer-implemented method of claim 1 in which one of the chat room summaries is designated by a user as an active chat room summary, said active chat room summary including a scrolling full-text display of an ongoing dialog by participants in the chat room, and wherein remaining additional chat room summaries. 7. The computer-implemented method of claim 6 in which each non-active chat room summary extends along a horizontal row of the display and the scrolling full-text display of the active chat room summary extends in a vertical column alongside the non-active chat room summaries. | 0.5 |
9,996,566 | 22 | 23 | 22. The system according to claim 21 and wherein said alternate visual data structures are a visual design structure consisting of a hierarchy of smart box elements. | 22. The system according to claim 21 and wherein said alternate visual data structures are a visual design structure consisting of a hierarchy of smart box elements. 23. The system according to claim 22 and wherein said hierarchy of smart box elements is based on semantic information extracted from at least one of: said hierarchy of components, inter component anchors and component editing history. | 0.5 |
7,814,109 | 16 | 17 | 16. The system according to claim 10 , wherein said token analysis module further selects a keyword of a pair of retrieved keywords, said selection based on an output value calculated for said each keyword of said pair of keywords, said selected keyword having a highest-ranked output value, repeats said selecting for at least one subsequent pair of retrieved keywords including said selected keyword to obtain said dominant keyword, and retrieves said at least one category associated with said dominant keyword from said keyword database. | 16. The system according to claim 10 , wherein said token analysis module further selects a keyword of a pair of retrieved keywords, said selection based on an output value calculated for said each keyword of said pair of keywords, said selected keyword having a highest-ranked output value, repeats said selecting for at least one subsequent pair of retrieved keywords including said selected keyword to obtain said dominant keyword, and retrieves said at least one category associated with said dominant keyword from said keyword database. 17. The system according to claim 16 , wherein said output value indicates a probability that said selected keyword is said dominant keyword. | 0.5 |
9,055,147 | 2 | 6 | 2. The method of claim 1 , wherein the voice input comprises a phonetic, short phrase input. | 2. The method of claim 1 , wherein the voice input comprises a phonetic, short phrase input. 6. The method of claim 2 , further comprising: matching the phonetic, short phrase input to a phonetic, short phrase response corresponding to a recognition grammar. | 0.727723 |
9,294,591 | 1 | 7 | 1. A method comprising: receiving, by a server comprising a processor, a request from a calling device for a call session with a terminating device over a communication network, wherein the request includes a fully qualified domain name identifying the calling device; transmitting to a domain naming server, by the server, a query comprising the fully qualified domain name; receiving, by the server, a response from the domain naming server; analyzing, by the server, the response that is received to determine an answer combination; transmitting to the calling device, by the server, a first response message via an internet protocol version 4 address if the answer combination comprises the internet protocol version 4 address with a first non-error indicator and an internet protocol version 6 address with a first error indicator; and transmitting to the calling device, by the server, a second response message via the internet protocol version 6 address if the answer combination comprises the internet protocol version 4 address with a second error indicator and the internet protocol version 6 address with a second non-error indicator. | 1. A method comprising: receiving, by a server comprising a processor, a request from a calling device for a call session with a terminating device over a communication network, wherein the request includes a fully qualified domain name identifying the calling device; transmitting to a domain naming server, by the server, a query comprising the fully qualified domain name; receiving, by the server, a response from the domain naming server; analyzing, by the server, the response that is received to determine an answer combination; transmitting to the calling device, by the server, a first response message via an internet protocol version 4 address if the answer combination comprises the internet protocol version 4 address with a first non-error indicator and an internet protocol version 6 address with a first error indicator; and transmitting to the calling device, by the server, a second response message via the internet protocol version 6 address if the answer combination comprises the internet protocol version 4 address with a second error indicator and the internet protocol version 6 address with a second non-error indicator. 7. The method of claim 1 , wherein the calling device is enabled for dual stack internet protocol addressing. | 0.831269 |
8,515,985 | 15 | 18 | 15. A device including: a memory storing instructions; and one or more processors to execute the instructions to: identify one or more candidate query refinements for a query based on one or more previous queries submitted by one or more users; generate, based on the one or more candidate query refinements, one or more term occurrence scores associated with one or more respective terms in the one or more candidate query refinements, the one or more term occurrence scores indicating a frequency of the one or more respective terms within in the one or more candidate query refinements; calculate, based on the one or more term occurrence scores, a respective query refinement score for each of the one or more candidate query refinements; generate, for a particular candidate query refinement of the one or more candidate query refinements, a first refinement count, the first refinement count being based on a frequency of occurrence of the particular candidate query refinement in a log; generate, for the particular candidate query refinement, a second refinement count, the second refinement count being based on a frequency of occurrence of another candidate query refinement, of the one or more candidate query refinements, in the log; generate, based on the first refinement count and the second refinement count, a query refinement popularity score for the particular candidate query refinement; and store information associating the respective query refinement score with each of the one or more candidate query refinements and the query refinement popularity score with the particular candidate query refinement for use in selecting among the one or more candidate query refinements for the given query. | 15. A device including: a memory storing instructions; and one or more processors to execute the instructions to: identify one or more candidate query refinements for a query based on one or more previous queries submitted by one or more users; generate, based on the one or more candidate query refinements, one or more term occurrence scores associated with one or more respective terms in the one or more candidate query refinements, the one or more term occurrence scores indicating a frequency of the one or more respective terms within in the one or more candidate query refinements; calculate, based on the one or more term occurrence scores, a respective query refinement score for each of the one or more candidate query refinements; generate, for a particular candidate query refinement of the one or more candidate query refinements, a first refinement count, the first refinement count being based on a frequency of occurrence of the particular candidate query refinement in a log; generate, for the particular candidate query refinement, a second refinement count, the second refinement count being based on a frequency of occurrence of another candidate query refinement, of the one or more candidate query refinements, in the log; generate, based on the first refinement count and the second refinement count, a query refinement popularity score for the particular candidate query refinement; and store information associating the respective query refinement score with each of the one or more candidate query refinements and the query refinement popularity score with the particular candidate query refinement for use in selecting among the one or more candidate query refinements for the given query. 18. The device of claim 15 , where the one or more processors are further to: generate, for the particular candidate query refinement, the respective query refinement score using: a sum of term occurrence scores of individual terms within the particular candidate query refinement, and a number of individual terms within the particular candidate query refinement. | 0.5 |
9,836,994 | 23 | 25 | 23. A method of simulating welding activity, the method comprising: tracking a welding tool manipulated by a user to determine movement and orientation of the welding tool relative to a welding coupon during a simulated welding operation; generating a simulated welding surface for the welding coupon; displaying the simulated welding surface on a display device disposed in a helmet; generating a simulated weld puddle having real-time molten metal fluidity and real-time heat dissipation characteristics on the simulated welding surface during the simulated welding operation; displaying the simulated weld puddle on the display device; generating a simulated weld bead based on the simulated weld puddle; and displaying the simulated weld bead on the display device. | 23. A method of simulating welding activity, the method comprising: tracking a welding tool manipulated by a user to determine movement and orientation of the welding tool relative to a welding coupon during a simulated welding operation; generating a simulated welding surface for the welding coupon; displaying the simulated welding surface on a display device disposed in a helmet; generating a simulated weld puddle having real-time molten metal fluidity and real-time heat dissipation characteristics on the simulated welding surface during the simulated welding operation; displaying the simulated weld puddle on the display device; generating a simulated weld bead based on the simulated weld puddle; and displaying the simulated weld bead on the display device. 25. The method of claim 23 , further comprising: generating the simulated weld puddle by generating a simulated welding arc between the welding tool and the simulated welding surface and simulating creation of the simulated weld puddle based on the simulated welding arc. | 0.5 |
9,817,809 | 17 | 18 | 17. The method of claim 16 , wherein identifying a correct interpretation further comprises triggering a disambiguation unit that is triggered by the ambiguity between the first word and the second word and generating a voice prompt to a user with each of the first word and the second word and the piece of information associated with the first word and the second word to identify the correct interpretation for the received word. | 17. The method of claim 16 , wherein identifying a correct interpretation further comprises triggering a disambiguation unit that is triggered by the ambiguity between the first word and the second word and generating a voice prompt to a user with each of the first word and the second word and the piece of information associated with the first word and the second word to identify the correct interpretation for the received word. 18. The method of claim 17 , wherein the piece of information associated with the first word and the second word further comprises a phrase that disambiguates the first word from the second word. | 0.505076 |
9,146,724 | 9 | 12 | 9. A non-transitory computer readable storage medium storing a set of instructions comprising: program instructions to extract first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of a first software program on a data processing system; program instructions to extract second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of a second software program on the data processing system; program instructions to generate a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; program instructions to determine whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; program instructions to generate a user interface notification in response to determining that the installation violates any constraint in the third set of constraints; and program instructions to transform the first metadata and the second metadata into a constraint language selected from a group of languages consisting of: unified modeling language (UML), object constraint language (OCL), and JAVA. | 9. A non-transitory computer readable storage medium storing a set of instructions comprising: program instructions to extract first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of a first software program on a data processing system; program instructions to extract second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of a second software program on the data processing system; program instructions to generate a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; program instructions to determine whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; program instructions to generate a user interface notification in response to determining that the installation violates any constraint in the third set of constraints; and program instructions to transform the first metadata and the second metadata into a constraint language selected from a group of languages consisting of: unified modeling language (UML), object constraint language (OCL), and JAVA. 12. The non-transitory computer readable storage medium of claim 9 , wherein the first software program and the second software program interact with one another. | 0.741214 |
9,058,407 | 2 | 3 | 2. The computer-readable medium of claim 1 , wherein the plurality of editing entries permit storing a plurality of versions of the database object without storing multiple separate copies of the database object, and wherein the plurality of editing entries permit restoring a selected version of the database object from a previous point in time without restoring intermediate versions of the database object. | 2. The computer-readable medium of claim 1 , wherein the plurality of editing entries permit storing a plurality of versions of the database object without storing multiple separate copies of the database object, and wherein the plurality of editing entries permit restoring a selected version of the database object from a previous point in time without restoring intermediate versions of the database object. 3. The computer-readable medium of claim 2 , where the editing entry describes a deletion from the set of metadata attributes. | 0.5 |
8,051,139 | 1 | 7 | 1. A non-transitory computer-readable medium encoding instructions which, when executed by a computer system, cause the computer system to: parse an electronic text document to generate a document vector for the electronic text document, wherein the document vector includes a feature count component and a feature position component, wherein the feature count component includes a plurality of feature count indicators for the electronic text document, wherein the feature position component includes a data structure selected from a group consisting of an ordered list and a tree of document substructure indicators, each document substructure indicator denoting a type of substructure in the electronic text document, and wherein a position of said each document substructure indicator in the data structure characterizes a position of a corresponding substructure in the electronic text document; determine a plurality of composite hyperspace distances between the document vector and a plurality of reference vectors, each composite hyperspace distance being defined between the document vector and a reference vector of the plurality of reference vectors, wherein each composite hyperspace distance is a function of a Euclidean-space distance dependent on the feature count component of the document vector and of an edit distance dependent on the feature position component of the document vector; and classify the electronic text document according to at least one of the plurality of composite hyperspace distances. | 1. A non-transitory computer-readable medium encoding instructions which, when executed by a computer system, cause the computer system to: parse an electronic text document to generate a document vector for the electronic text document, wherein the document vector includes a feature count component and a feature position component, wherein the feature count component includes a plurality of feature count indicators for the electronic text document, wherein the feature position component includes a data structure selected from a group consisting of an ordered list and a tree of document substructure indicators, each document substructure indicator denoting a type of substructure in the electronic text document, and wherein a position of said each document substructure indicator in the data structure characterizes a position of a corresponding substructure in the electronic text document; determine a plurality of composite hyperspace distances between the document vector and a plurality of reference vectors, each composite hyperspace distance being defined between the document vector and a reference vector of the plurality of reference vectors, wherein each composite hyperspace distance is a function of a Euclidean-space distance dependent on the feature count component of the document vector and of an edit distance dependent on the feature position component of the document vector; and classify the electronic text document according to at least one of the plurality of composite hyperspace distances. 7. The computer-readable medium of claim 1 , wherein the electronic text document is an electronic mail message. | 0.832836 |
7,904,451 | 1 | 3 | 1. A method of content management comprising: retrieving a data record associated with a product object instance from a database in response to a first selection of the product object instance; retrieving an audience profile from the database in response to a second selection of the audience profile, the selected audience profile including a plurality of audience factors; converting at least a portion of the data record into a structured format file supporting a plurality of rhetorical elements, wherein the portion of the data record converted into a structured format file is based on the selected audience profile; and rendering an electronically displayable document using the structured format file, the rendering of the electronically displayable document based on assembly rules selected from a plurality of assembly rules, wherein the assembly rules are selected based on the plurality of audience factors of the selected audience profile. | 1. A method of content management comprising: retrieving a data record associated with a product object instance from a database in response to a first selection of the product object instance; retrieving an audience profile from the database in response to a second selection of the audience profile, the selected audience profile including a plurality of audience factors; converting at least a portion of the data record into a structured format file supporting a plurality of rhetorical elements, wherein the portion of the data record converted into a structured format file is based on the selected audience profile; and rendering an electronically displayable document using the structured format file, the rendering of the electronically displayable document based on assembly rules selected from a plurality of assembly rules, wherein the assembly rules are selected based on the plurality of audience factors of the selected audience profile. 3. The method of claim 1 , wherein the structured format file includes data record set coding. | 0.9 |
9,411,889 | 25 | 26 | 25. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: partitioning a set of monotonically ordered document identification tags into a plurality of segments, each segment associated with a respective subset of the set of monotonically ordered document identification tags; subdividing each of the segments into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about a new document, the information including a value of the query-independent document importance metric and a globally unique document identifier for the new document; selecting, based at least in part on the globally unique document identifier, one of the segments; selecting, based at least on the query-independent information, one of the tiers associated with the selected segment; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in a collection of documents; repeating the receiving, selecting a segment, selecting a tier, and assigning, with respect to one or more additional new documents; and wherein the assigned document identification tags are assigned to documents in the collection of documents having globally unique document identifiers associated with the respective segment. | 25. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: partitioning a set of monotonically ordered document identification tags into a plurality of segments, each segment associated with a respective subset of the set of monotonically ordered document identification tags; subdividing each of the segments into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about a new document, the information including a value of the query-independent document importance metric and a globally unique document identifier for the new document; selecting, based at least in part on the globally unique document identifier, one of the segments; selecting, based at least on the query-independent information, one of the tiers associated with the selected segment; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in a collection of documents; repeating the receiving, selecting a segment, selecting a tier, and assigning, with respect to one or more additional new documents; and wherein the assigned document identification tags are assigned to documents in the collection of documents having globally unique document identifiers associated with the respective segment. 26. The non-transitory computer readable storage medium of claim 25 , wherein each tier in the plurality of tiers is associated with a respective predetermined range of metric values; and wherein instructions for selecting a tier comprise instructions for selecting the tier for which the query-independent information of the new document falls within the respective predetermined range of metric values associated with the selected tier. | 0.663077 |
8,798,521 | 1 | 3 | 1. A method for creating content in an online learning environment, comprising: creating a topic for discussion between a plurality of participants in an online learning environment, wherein the topic for discussion includes a title; receiving tagged content over a network, the tagged content received from a computing device associated with a participant from the plurality of participants, wherein the tagged content is associated with the topic for discussion; receiving descriptive information from the participant regarding the tagged content; and executing instructions stored in memory, wherein execution of the instructions by a processor: publishes the tagged content into a forum of the online learning environment for discussion; and updates the forum with feedback received from one or more participants in the online learning environment in response to the tagged content, wherein the topic for discussion, associated tagged content, descriptive information, and received feedback form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment. | 1. A method for creating content in an online learning environment, comprising: creating a topic for discussion between a plurality of participants in an online learning environment, wherein the topic for discussion includes a title; receiving tagged content over a network, the tagged content received from a computing device associated with a participant from the plurality of participants, wherein the tagged content is associated with the topic for discussion; receiving descriptive information from the participant regarding the tagged content; and executing instructions stored in memory, wherein execution of the instructions by a processor: publishes the tagged content into a forum of the online learning environment for discussion; and updates the forum with feedback received from one or more participants in the online learning environment in response to the tagged content, wherein the topic for discussion, associated tagged content, descriptive information, and received feedback form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment. 3. The method of claim 1 , wherein feedback regarding the topic for discussion may not be received after an expiration date associated with the topic for discussion. | 0.5 |
10,142,708 | 2 | 6 | 2. The method of claim 1 , further comprising: generating a narrative path graph specific to the user and the respective narrative, the narrative path graph comprising a plurality of nodes and at least one edge which extends between respective pairs of the nodes, by the at least one processor-based component, each of the nodes corresponding to a respective one of the narrative segments of the respective narrative, and each of the at least one edge indicative of the respective presentation sequence in which the respective narrative segments of the respective presentation of the respective narrative were actually presented to the respective user. | 2. The method of claim 1 , further comprising: generating a narrative path graph specific to the user and the respective narrative, the narrative path graph comprising a plurality of nodes and at least one edge which extends between respective pairs of the nodes, by the at least one processor-based component, each of the nodes corresponding to a respective one of the narrative segments of the respective narrative, and each of the at least one edge indicative of the respective presentation sequence in which the respective narrative segments of the respective presentation of the respective narrative were actually presented to the respective user. 6. The method of claim 2 , further comprising: identifying, by the at least one processor-based component, at least one candidate for the user to share with based at least in part on the narrative path graph specific to the user and the respective narrative. | 0.730689 |
8,239,189 | 8 | 9 | 8. The method of claim 1 , comprising changing the sentiment dictionary as a function of the search query. | 8. The method of claim 1 , comprising changing the sentiment dictionary as a function of the search query. 9. The method of claim 8 , wherein the changing of the sentiment dictionary comprises removing adjectives associated to a group context from the sentiment dictionary if the group context of the adjective does not correspond to terms used in the search query. | 0.5 |
8,090,709 | 1 | 6 | 1. A method in a computing device for determining similarity between queries, the method comprising: storing frequencies of the queries during intervals, each frequency of a query for an interval representing a number of times the query was submitted by users to a search engine; for each of the queries, generating autoregressive integrated moving average (“ARIMA”) coefficients for that query based on the stored frequencies for that query; and for a pair of queries, calculating a similarity score for the queries based on a correlation between the ARIMA coefficients of the queries, the calculating including aggregating products, for each ARIMA coefficients, of a first factor of a first query of the pair and a second factor of a second query of the pair, a factor for an ARIMA coefficient of a query being a difference between the ARIMA coefficient and a mean of the ARIMA coefficients divided by a standard deviation of the ARIMA coefficients. | 1. A method in a computing device for determining similarity between queries, the method comprising: storing frequencies of the queries during intervals, each frequency of a query for an interval representing a number of times the query was submitted by users to a search engine; for each of the queries, generating autoregressive integrated moving average (“ARIMA”) coefficients for that query based on the stored frequencies for that query; and for a pair of queries, calculating a similarity score for the queries based on a correlation between the ARIMA coefficients of the queries, the calculating including aggregating products, for each ARIMA coefficients, of a first factor of a first query of the pair and a second factor of a second query of the pair, a factor for an ARIMA coefficient of a query being a difference between the ARIMA coefficient and a mean of the ARIMA coefficients divided by a standard deviation of the ARIMA coefficients. 6. The method of claim 1 wherein the generating of the ARIMA coefficients generates the same number of coefficients for each query. | 0.610119 |
8,594,023 | 15 | 16 | 15. A computer program product comprising: a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. | 15. A computer program product comprising: a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. 16. The computer program product of claim 15 , wherein the method further comprises probing the spectrum band for a data transmission drift associated with the current working mode of the primary user, wherein the scheduling transmissions on the spectrum band is further responsive to the data transmission drift associated with the current working mode of the primary user. | 0.5 |
7,548,913 | 11 | 20 | 11. One or more machine-readable storage media containing instructions for use in generating a report from multiple sources, the one or more machine-readable storage media being one or more tangible media, the instructions being executable by one or more processing devices to: obtain a topic by processing input queries relating to the topic, the input queries corresponding to queries from multiple users made over a predefined period of time; obtain information about the topic from the multiple sources, the information comprising excerpts from the multiple sources that meet one or more criteria; wherein obtaining the information comprises: if the topic is ambiguous, disambiguating the topic by combining names of the one or more categories with the topic, thereby producing a disambiguated topic and formulating a search query based on the disambiguated topic; if the topic is not ambiguous, formulating the search query based on the topic; and searching the multiple sources using the search query to obtain the information; and generate the report using the excerpts, wherein generating the report comprises: obtaining subtopics by analyzing the excerpts from the multiple sources for commonalities; organizing the excerpts and hyperlinks associated with the excerpts under appropriate subtopics to provide a narrative flow relating to the topic, the excerpts being organized by subtopic and, in a subtopic, being organized in an order; and editing text in the excerpts, wherein editing comprises editing text in excerpts so that excerpts from different sources under subtopics read more like the excerpts from different sources came from a single source; and display the report. | 11. One or more machine-readable storage media containing instructions for use in generating a report from multiple sources, the one or more machine-readable storage media being one or more tangible media, the instructions being executable by one or more processing devices to: obtain a topic by processing input queries relating to the topic, the input queries corresponding to queries from multiple users made over a predefined period of time; obtain information about the topic from the multiple sources, the information comprising excerpts from the multiple sources that meet one or more criteria; wherein obtaining the information comprises: if the topic is ambiguous, disambiguating the topic by combining names of the one or more categories with the topic, thereby producing a disambiguated topic and formulating a search query based on the disambiguated topic; if the topic is not ambiguous, formulating the search query based on the topic; and searching the multiple sources using the search query to obtain the information; and generate the report using the excerpts, wherein generating the report comprises: obtaining subtopics by analyzing the excerpts from the multiple sources for commonalities; organizing the excerpts and hyperlinks associated with the excerpts under appropriate subtopics to provide a narrative flow relating to the topic, the excerpts being organized by subtopic and, in a subtopic, being organized in an order; and editing text in the excerpts, wherein editing comprises editing text in excerpts so that excerpts from different sources under subtopics read more like the excerpts from different sources came from a single source; and display the report. 20. The one or more machine-readable storage media of claim 11 , wherein editing text comprises at least one of: deleting words from a sentence based on at least one of a location of the words in the sentence and a location of the sentence in the excerpt; and adding words to a sentence based on a location of the sentence in the excerpt. | 0.534435 |
9,733,916 | 2 | 3 | 2. A method as in claim 1 further comprising: the engine receiving updated data of the external data source from the first external widget; the engine storing the updated data in the database; and the engine communicating the updated data to an other widget identified by a linking table. | 2. A method as in claim 1 further comprising: the engine receiving updated data of the external data source from the first external widget; the engine storing the updated data in the database; and the engine communicating the updated data to an other widget identified by a linking table. 3. A method as in claim 2 wherein the other widget comprises a second external widget in communication with a second outside data source. | 0.5 |
8,904,270 | 1 | 2 | 1. A method for automated electronic document distribution, comprising: receiving, by a processor of a computing device, a routing directive for the one or more document distributions, wherein receiving the routing directive comprises: receiving, by the processor, a selection from among one or more pre-existing electronic documents for inclusion in one or more document distributions, a selection of one or more recipients for the one or more document distributions, and a selection of a document format individually specified for each recipient, wherein each document format identifies the format of documents to be sent to the respective recipient such that the document format may be different among the recipients; generating, by the processor, a document distribution workflow comprising an instruction set for performing the one or more document distributions based at least in part on the routing directive; storing, by the processor, the instruction set; providing, by the processor, the scan cover sheet, wherein the scan cover sheet identifies the document distribution workflow; receiving, by the processor, one or more scanned documents and the scan cover sheet from a scanning device; identifying, by the processor, from the scan cover sheet received from the scanning device, the document distribution workflow; executing, by the processor, the instruction set associated with the document distribution workflow, wherein executing the instruction set comprises: transmitting, by the processor, the selected one or more pre-existing electronic documents, the one or more scanned documents and the scan cover sheet to the one or more recipients in accordance with the document distribution workflow, where such distribution is triggered by receipt of the one or more scanned documents. | 1. A method for automated electronic document distribution, comprising: receiving, by a processor of a computing device, a routing directive for the one or more document distributions, wherein receiving the routing directive comprises: receiving, by the processor, a selection from among one or more pre-existing electronic documents for inclusion in one or more document distributions, a selection of one or more recipients for the one or more document distributions, and a selection of a document format individually specified for each recipient, wherein each document format identifies the format of documents to be sent to the respective recipient such that the document format may be different among the recipients; generating, by the processor, a document distribution workflow comprising an instruction set for performing the one or more document distributions based at least in part on the routing directive; storing, by the processor, the instruction set; providing, by the processor, the scan cover sheet, wherein the scan cover sheet identifies the document distribution workflow; receiving, by the processor, one or more scanned documents and the scan cover sheet from a scanning device; identifying, by the processor, from the scan cover sheet received from the scanning device, the document distribution workflow; executing, by the processor, the instruction set associated with the document distribution workflow, wherein executing the instruction set comprises: transmitting, by the processor, the selected one or more pre-existing electronic documents, the one or more scanned documents and the scan cover sheet to the one or more recipients in accordance with the document distribution workflow, where such distribution is triggered by receipt of the one or more scanned documents. 2. The method of claim 1 , wherein the one or more pre-existing electronic documents, the one or more scanned documents and the scan cover sheet are transmitted to the one or more recipients upon creation of the one or more scanned documents. | 0.566308 |
7,533,034 | 48 | 49 | 48. The computer program product according to claim 47 wherein access to financial data is controlled through an employee's log-in for the computer network. | 48. The computer program product according to claim 47 wherein access to financial data is controlled through an employee's log-in for the computer network. 49. The computer program product according to claim 48 wherein if no financial data is available in a database associated with the network and the user enters financial data in a template the computer program product further comprises: computer code for adding the financial data to the database for a subsequent user suggestion. | 0.5 |
9,110,882 | 4 | 6 | 4. The method of claim 1 wherein converting the subset of the sentences to simplified assertion statements comprises marking up first ones of the sentences to identify unique specific entities, the unique specific entities including one or more of dates, currencies, quantities, or named entities. | 4. The method of claim 1 wherein converting the subset of the sentences to simplified assertion statements comprises marking up first ones of the sentences to identify unique specific entities, the unique specific entities including one or more of dates, currencies, quantities, or named entities. 6. The method of claim 4 wherein the unstructured text is included in a document, and the unique specific entities are identified within the document using Anaphora resolution. | 0.5 |
6,100,825 | 32 | 33 | 32. The invention as set forth in claim 31, wherein the minimum total cost is a least number of bits required to represent each data set. | 32. The invention as set forth in claim 31, wherein the minimum total cost is a least number of bits required to represent each data set. 33. The invention as set forth in claim 32, wherein the total cost is a total encoding cost of each decoding context associated with each data set plus the cost of representing codebooks for each of decoding context. | 0.5 |
7,683,916 | 7 | 8 | 7. A method performed by a computing system having a processor, comprising: under control of the processor, selecting a first template comprising a foreground image with at least one cutout region; producing a user-defined graphics edit by adjusting at least one parameter associated with a selected editable object; importing at least a part of the user-defined graphics edit into the cutout region of the first template; selecting a second template comprising a foreground image with at least one cutout region; and importing at least a part of the user-defined graphics edit into the cutout region of the second template. | 7. A method performed by a computing system having a processor, comprising: under control of the processor, selecting a first template comprising a foreground image with at least one cutout region; producing a user-defined graphics edit by adjusting at least one parameter associated with a selected editable object; importing at least a part of the user-defined graphics edit into the cutout region of the first template; selecting a second template comprising a foreground image with at least one cutout region; and importing at least a part of the user-defined graphics edit into the cutout region of the second template. 8. The method of claim 7 , wherein the at least one parameter comprises at least one of a position, a size, an orientation, a shape, a characteristic, a text a lettering, and a color value of the selected editable object. | 0.77449 |
9,098,568 | 1 | 11 | 1. A computer-implemented method, comprising: receiving at a client device a dictionary defining query triggers, each of the query triggers being one or more terms; identifying at the client device query triggers in a resource, the resource being a non-query resource; for each query trigger identified in the resource, calculating at the client device a rank score for the query trigger based on attributes of the query trigger, the attributes including at least one of: a context of the query trigger defined by a display format of the query trigger in the resource; and a frequency of occurrence of the query trigger in the resource; ranking at the client device the query triggers according to the rank scores; generating at the client device search query suggestions from the query triggers identified in the resource; and presenting at the client device the search query suggestions according to the ranking of the query triggers. | 1. A computer-implemented method, comprising: receiving at a client device a dictionary defining query triggers, each of the query triggers being one or more terms; identifying at the client device query triggers in a resource, the resource being a non-query resource; for each query trigger identified in the resource, calculating at the client device a rank score for the query trigger based on attributes of the query trigger, the attributes including at least one of: a context of the query trigger defined by a display format of the query trigger in the resource; and a frequency of occurrence of the query trigger in the resource; ranking at the client device the query triggers according to the rank scores; generating at the client device search query suggestions from the query triggers identified in the resource; and presenting at the client device the search query suggestions according to the ranking of the query triggers. 11. The computer-implemented method of claim 1 , wherein the attributes include the context of the query trigger and include the frequency of occurrence of the query trigger. | 0.869369 |
8,112,707 | 1 | 18 | 1. A method for determining information of interest of a user in an information source or a document corpus, comprising the steps of: determining a private ontology of the user, wherein the private ontology comprises definitions of semantic items, wherein each of said semantic items is classified into one of a thing, a type of thing, a characteristic, a value of a characteristic, and a way of relating things, and wherein the private ontology defines a relationship between the semantic items; capturing a reading style of the user, wherein said reading style is a set of one or more declared patterns from a training document, wherein each declared pattern identifies one of said semantic items in said private ontology, and wherein capturing reading style comprises: capturing said classification of each selected text sample within said information source into one of the semantic items defined by the user; and capturing relationship between the semantic items defined by the user; determining a reading plan of the user, wherein the reading plan comprises a set of reading plan steps defined by the user that identifies and controls evaluation sequence of text within one or more source documents within the information source; creating a worldview of the user using said reading style, said reading plan and said private ontology, wherein the worldview reflects a logic and structure with which a user comprehends a document; applying said worldview to said document corpus for determining said information of interest, wherein the information of interest is the information in the document corpus that semantically matches the information in the training document; and reporting the information of interest to the user. | 1. A method for determining information of interest of a user in an information source or a document corpus, comprising the steps of: determining a private ontology of the user, wherein the private ontology comprises definitions of semantic items, wherein each of said semantic items is classified into one of a thing, a type of thing, a characteristic, a value of a characteristic, and a way of relating things, and wherein the private ontology defines a relationship between the semantic items; capturing a reading style of the user, wherein said reading style is a set of one or more declared patterns from a training document, wherein each declared pattern identifies one of said semantic items in said private ontology, and wherein capturing reading style comprises: capturing said classification of each selected text sample within said information source into one of the semantic items defined by the user; and capturing relationship between the semantic items defined by the user; determining a reading plan of the user, wherein the reading plan comprises a set of reading plan steps defined by the user that identifies and controls evaluation sequence of text within one or more source documents within the information source; creating a worldview of the user using said reading style, said reading plan and said private ontology, wherein the worldview reflects a logic and structure with which a user comprehends a document; applying said worldview to said document corpus for determining said information of interest, wherein the information of interest is the information in the document corpus that semantically matches the information in the training document; and reporting the information of interest to the user. 18. The method of claim 1 , wherein the reading plan sets a start and a length of text in the document from which the information of interest is to be extracted. | 0.748438 |
10,133,731 | 1 | 18 | 1. A computer-implemented method for generating a summary of a digital text, the method executable on a server, the server coupled to a communication network, the method comprising: acquiring by the server, an indication of the digital text to be processed, the digital text comprising a plurality of sentences; parsing by the server, each of plurality of sentences into one or more concept phrases, each of the one or more concept phrases having at least one word; the parsing being executed by applying at least one parsing parameter; executing, by the server, a first analysis to generate a context-independent relation (CIR) value for a given concept phrase of the one or more concept phrases, the CIR value representing a first ratio of a co-inclusion of: (i) at least one word of the given concept phrase and (ii) at least one word of each of the remaining concept phrases of the one or more concept phrases; executing, by the server, a second analysis to generate a context-dependent relation (CDR) value for the given concept phrase, the CDR value representing a second ratio of: (i) a number of sentences where the given concept phrase co-occurs with another concept phrase of the one or more concept phrases to (ii) a total number of the plurality of sentences containing the other concept phrase within the digital text; determining by the server, a total CIR weight and a total CDR weight for each of the concept phrases; determining by the server, for each of the concept phrase, a concept meaning value, based at least in part on its respective total CIR weight and the total CDR weight; determining by the server, for a given sentence of the plurality of sentences, a sentence meaning value, based at least in part of the concept meaning value of each concept phrase contained in the given sentence; ranking by the server, each sentence based at least on the determined sentence meaning value; and, generating by the server, the summary of the digital text, the summary of the digital text comprising at least one sentence extracted from the digital text based on its determined ranking. | 1. A computer-implemented method for generating a summary of a digital text, the method executable on a server, the server coupled to a communication network, the method comprising: acquiring by the server, an indication of the digital text to be processed, the digital text comprising a plurality of sentences; parsing by the server, each of plurality of sentences into one or more concept phrases, each of the one or more concept phrases having at least one word; the parsing being executed by applying at least one parsing parameter; executing, by the server, a first analysis to generate a context-independent relation (CIR) value for a given concept phrase of the one or more concept phrases, the CIR value representing a first ratio of a co-inclusion of: (i) at least one word of the given concept phrase and (ii) at least one word of each of the remaining concept phrases of the one or more concept phrases; executing, by the server, a second analysis to generate a context-dependent relation (CDR) value for the given concept phrase, the CDR value representing a second ratio of: (i) a number of sentences where the given concept phrase co-occurs with another concept phrase of the one or more concept phrases to (ii) a total number of the plurality of sentences containing the other concept phrase within the digital text; determining by the server, a total CIR weight and a total CDR weight for each of the concept phrases; determining by the server, for each of the concept phrase, a concept meaning value, based at least in part on its respective total CIR weight and the total CDR weight; determining by the server, for a given sentence of the plurality of sentences, a sentence meaning value, based at least in part of the concept meaning value of each concept phrase contained in the given sentence; ranking by the server, each sentence based at least on the determined sentence meaning value; and, generating by the server, the summary of the digital text, the summary of the digital text comprising at least one sentence extracted from the digital text based on its determined ranking. 18. The method of claim 1 , wherein the executing the first analysis to generate the context-independent relation (CIR) value for the given concept phrase relative to a target phrase which is another one of the one or more concept phrases comprises: (i) determining a number of words of the given concept phrase that are also present in the target phrase and (ii) dividing the number of co-occurring words by a total number of words in the target phrase. | 0.615254 |
8,594,422 | 14 | 15 | 14. The system of claim 13 wherein the text identifying component identifies the white space regions by: selecting one or more rectangular white space candidate seeds that are candidate white space regions, said white space candidate seeds being located in inter-word spaces between neighboring, vertically overlapping word bounding boxes and having a width greater than a threshold width; vertically expanding each white space candidate seed by a configurable amount; selecting expanded white space candidate seeds that do not intersect any word bounding boxes as white space seeds; horizontally expanding the white space seeds without overlapping any word bounding boxes; and vertically expanding the horizontally expanded white space seeds while horizontally shrinking any vertically and horizontally expanded white space seeds to prevent overlap with any word bounding boxes. | 14. The system of claim 13 wherein the text identifying component identifies the white space regions by: selecting one or more rectangular white space candidate seeds that are candidate white space regions, said white space candidate seeds being located in inter-word spaces between neighboring, vertically overlapping word bounding boxes and having a width greater than a threshold width; vertically expanding each white space candidate seed by a configurable amount; selecting expanded white space candidate seeds that do not intersect any word bounding boxes as white space seeds; horizontally expanding the white space seeds without overlapping any word bounding boxes; and vertically expanding the horizontally expanded white space seeds while horizontally shrinking any vertically and horizontally expanded white space seeds to prevent overlap with any word bounding boxes. 15. The system of claim 14 wherein the text identifying component merges at least white space seeds that overlap one another into a single white space seed. | 0.859964 |
7,940,273 | 1 | 3 | 1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. | 1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. 3. The method of claim 1 , wherein converting the glyph includes searching a character mapping table using the glyph as input, and for obtaining the Unicode representation of the input glyph. | 0.505181 |
8,332,220 | 9 | 11 | 9. The method of claim 7 further comprising creating a session document from a presentation document, including: identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; identifying a user participant for the presentation, the user participant having a user profile comprising user classifications; and filtering the structured document in dependence upon the user classifications and the classification identifiers. | 9. The method of claim 7 further comprising creating a session document from a presentation document, including: identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; identifying a user participant for the presentation, the user participant having a user profile comprising user classifications; and filtering the structured document in dependence upon the user classifications and the classification identifiers. 11. The method of claim 9 further comprising creating a presentation document, including: creating, in dependence upon an original document, a structured document comprising one or more structural elements; classifying a structural element of the structured document according to a presentation attribute; and creating a presentation grammar for the structured document, wherein the presentation grammar for the structured document includes grammar elements each of which includes an identifier for at least one structural element of the structured document. | 0.5 |
10,073,841 | 12 | 14 | 12. The method of claim 9 , wherein the generating of the message comprises: for each lexical slot in the plurality of lexical slots: accessing the corpus of source data corresponding to the lexical slot; selecting a term from the corpus of source data in accordance with the grammatical constraint corresponding to the lexical slot; and populating the lexical slot with the selected term. | 12. The method of claim 9 , wherein the generating of the message comprises: for each lexical slot in the plurality of lexical slots: accessing the corpus of source data corresponding to the lexical slot; selecting a term from the corpus of source data in accordance with the grammatical constraint corresponding to the lexical slot; and populating the lexical slot with the selected term. 14. The method of claim 12 , wherein the generating of the message further comprises appending an octothorpe to the selected term prior to populating the lexical slot. | 0.5 |
9,495,460 | 1 | 12 | 1. A method at an information retrieval system arranged to retrieve results from a plurality of different sources comprising: at an input, receiving a query; at an output, issuing the query to the plurality of different sources, at least one of which is a public domain search engine and at least one of which is a private domain search engine; at the input, receiving a results list from each of the plurality of different sources; determining whether to merge said results lists based on a relevancy determination made using a merging model; forming, by a processor, a complete results list from the received results lists using the merging model, forming the complete results list comprising forming a merged results list using a merging model in a data structure comprising a plurality of weighted event variables describing a complete results list presentation event, the merging model comprising a decision process that determines whether or not to merge results based on the relevance of the results, the decision process deciding to not merge results when a difference between a first measure of relevance of a first set of results and a second measure of relevance of a second set of results satisfies a threshold condition; arranging a user interface to present the complete results list; observing user behavior in response to the presented complete results list; and using the observed user behavior to update the merging model. | 1. A method at an information retrieval system arranged to retrieve results from a plurality of different sources comprising: at an input, receiving a query; at an output, issuing the query to the plurality of different sources, at least one of which is a public domain search engine and at least one of which is a private domain search engine; at the input, receiving a results list from each of the plurality of different sources; determining whether to merge said results lists based on a relevancy determination made using a merging model; forming, by a processor, a complete results list from the received results lists using the merging model, forming the complete results list comprising forming a merged results list using a merging model in a data structure comprising a plurality of weighted event variables describing a complete results list presentation event, the merging model comprising a decision process that determines whether or not to merge results based on the relevance of the results, the decision process deciding to not merge results when a difference between a first measure of relevance of a first set of results and a second measure of relevance of a second set of results satisfies a threshold condition; arranging a user interface to present the complete results list; observing user behavior in response to the presented complete results list; and using the observed user behavior to update the merging model. 12. A method as claimed in claim 1 , which further comprises: arranging an evaluator to evaluate the merging model at intervals; and modifying the merging model on the basis of the evaluation. | 0.756962 |
9,398,460 | 1 | 3 | 1. A mobile phone-based system for providing on-demand security to a requester primarily via non-voice communication, the system comprising: a. a database having i. requester data, ii. security escort data, iii. engagement data, iv. review data, and v. at least one request factor; b. at least one requester mobile phone having i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. request security escorts for at least one time period in at least one location, B. select at least one request factor and send a request to an engagement engine, C. receive a response from the engagement engine, D. enable the requester to meet and identify an escort, E. declare an emergency, F. terminate security escort for one time period in one location, and G. close an engagement; c. a screening facility adapted to— i. qualify at least one selected from security escort, requester, and ii. review qualifications of at least are selected from escort and requestor; d. at least one security escort mobile phone having— i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. receive a proposed security engagement, B. respond to the proposed engagement, C. receive security escort details, D. enable an escort to meet and identify a requester, E. declare an emergency, and F. close an engagement; e. an engagement engine having— i. a query generator interactively facilitating each request and generating a query most closely related to the requester's needs in view of each applicable request factor, and ii. a response generator receiving the query and applying request factors to generate a response including confirmation of request, expected cost, and escort identification; f. a meeting engine adapted to— i. transmit location and identification data to the requester and escort, ii. facilitate a meeting between the requester and the escort, iii. receive verification of an agreeable meeting, iv. close each engagement upon notification from at least one selected from requester and escort database, and v. pay the escorts whereby the security escorts required for a particular engagement are determined based on requester-provided data as a function of a requester requirements, security escort provider abilities, and application of request factors. | 1. A mobile phone-based system for providing on-demand security to a requester primarily via non-voice communication, the system comprising: a. a database having i. requester data, ii. security escort data, iii. engagement data, iv. review data, and v. at least one request factor; b. at least one requester mobile phone having i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. request security escorts for at least one time period in at least one location, B. select at least one request factor and send a request to an engagement engine, C. receive a response from the engagement engine, D. enable the requester to meet and identify an escort, E. declare an emergency, F. terminate security escort for one time period in one location, and G. close an engagement; c. a screening facility adapted to— i. qualify at least one selected from security escort, requester, and ii. review qualifications of at least are selected from escort and requestor; d. at least one security escort mobile phone having— i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. receive a proposed security engagement, B. respond to the proposed engagement, C. receive security escort details, D. enable an escort to meet and identify a requester, E. declare an emergency, and F. close an engagement; e. an engagement engine having— i. a query generator interactively facilitating each request and generating a query most closely related to the requester's needs in view of each applicable request factor, and ii. a response generator receiving the query and applying request factors to generate a response including confirmation of request, expected cost, and escort identification; f. a meeting engine adapted to— i. transmit location and identification data to the requester and escort, ii. facilitate a meeting between the requester and the escort, iii. receive verification of an agreeable meeting, iv. close each engagement upon notification from at least one selected from requester and escort database, and v. pay the escorts whereby the security escorts required for a particular engagement are determined based on requester-provided data as a function of a requester requirements, security escort provider abilities, and application of request factors. 3. The system of claim 1 , where the database records include categories of engagements based on factors including at least one of: engagement, location, duration, date, time, number of escorts, escort training, armed, uniformed, gender, and transportation. | 0.5 |
9,442,810 | 6 | 10 | 6. A method to enable visual management of a service, the method comprising: receiving a specification of an abstract type of a resource on which the service is to be deployed; generating a visual representation of the abstract type of the resource for presentation in a user interface; identifying concrete types of resources in an infrastructure environment that correspond to the abstract type of the resource; generating, using one or more processors, visual representations of the concrete types of resources for presentation in the user interface; receiving a command to establish a mapping between the abstract type of the resource and one of the concrete types of resources; establishing a binding between the abstract type of the resource and one of the instances of the actual resources, the one of the instances of the actual resources selected from the infrastructure environment based on the establishing of the mapping between the abstract type of the resource and the one of the concrete types of the resources, the establishing of the binding between the abstract type of the resource and one of the instances of the actual resources being performed automatically based on a set of policies for minimizing resource consumption but maintaining service-level agreements; generating a visual representation of the binding between the abstract type of the resource and the one of the instances of the actual resources; sending a request to a management system to allocate the one of the instances of the actual resources for deploying of the service; and sending a command to a management system to deploy the service such that the service uses the one of the instances of the actual resources. | 6. A method to enable visual management of a service, the method comprising: receiving a specification of an abstract type of a resource on which the service is to be deployed; generating a visual representation of the abstract type of the resource for presentation in a user interface; identifying concrete types of resources in an infrastructure environment that correspond to the abstract type of the resource; generating, using one or more processors, visual representations of the concrete types of resources for presentation in the user interface; receiving a command to establish a mapping between the abstract type of the resource and one of the concrete types of resources; establishing a binding between the abstract type of the resource and one of the instances of the actual resources, the one of the instances of the actual resources selected from the infrastructure environment based on the establishing of the mapping between the abstract type of the resource and the one of the concrete types of the resources, the establishing of the binding between the abstract type of the resource and one of the instances of the actual resources being performed automatically based on a set of policies for minimizing resource consumption but maintaining service-level agreements; generating a visual representation of the binding between the abstract type of the resource and the one of the instances of the actual resources; sending a request to a management system to allocate the one of the instances of the actual resources for deploying of the service; and sending a command to a management system to deploy the service such that the service uses the one of the instances of the actual resources. 10. The method of claim 6 , further comprising displaying a view of a data center from a perspective of at least one of the service, the one of the instances of the actual resources, and a business. | 0.655052 |
9,183,196 | 12 | 15 | 12. The system of claim 11 , wherein: determining each parsing initialization comprises replacing, for each annotation, the annotated n-grams of the command input sentence with a non-terminal of the entity type of the annotation service. | 12. The system of claim 11 , wherein: determining each parsing initialization comprises replacing, for each annotation, the annotated n-grams of the command input sentence with a non-terminal of the entity type of the annotation service. 15. The system of claim 12 , wherein: each non-terminal type corresponds to a variable for the action; and for each non-terminal type, a semantic yield of a non-terminal of the non-terminal type defines an argument of the variable for the action. | 0.676316 |
8,112,702 | 1 | 9 | 1. The method for managing annotations associated with a first video, the method comprising: receiving a plurality of annotations for one or more intervals of the first video, each annotation having a reputation score associated with a user providing the annotation; assigning a weight to each annotation based on the reputation score; forming a plurality of groups, each group including annotations for intervals of the first video that are similar to each other; determining a first group having related annotations based on the assigned weights of the annotations; and forming a first annotated clip of the first video based upon the intervals in the first group. | 1. The method for managing annotations associated with a first video, the method comprising: receiving a plurality of annotations for one or more intervals of the first video, each annotation having a reputation score associated with a user providing the annotation; assigning a weight to each annotation based on the reputation score; forming a plurality of groups, each group including annotations for intervals of the first video that are similar to each other; determining a first group having related annotations based on the assigned weights of the annotations; and forming a first annotated clip of the first video based upon the intervals in the first group. 9. The method of claim 1 , wherein forming the plurality of groups comprises: identifying a plurality of scenes in the first video; and associating each group with one or more scenes. | 0.867965 |
9,904,768 | 9 | 14 | 9. An apparatus comprising: at least one processor; and at least one memory storing processor-executable instructions that, when executed by the at least one processor, perform a method of analyzing a text documenting a patient encounter, the method comprising: analyzing the text to identify a set of one or more features of at least a portion of the text; correlating the set of one or more features to a set of alternative hypotheses for an abstract semantic concept representing an intended semantic meaning of the at least a portion of the text; computing, using at least one statistical model implemented using at least one processor and for each of at least some of the alternative hypotheses of the set, one or more measures of estimated likelihood that the respective alternative hypothesis accurately represents the intended semantic meaning of the at least a portion of the text; identifying hypotheses, including some or all of the at least some of the alternative hypotheses, to be presented to a user, wherein identifying the hypotheses comprises, for each of the at least some of the alternative hypotheses of the set: in response to determining that the one or more measures of estimated likelihood for the alternative hypothesis satisfy one or more criteria, identifying that the alternative hypothesis is to be presented to the user; and presenting the identified hypotheses, to the user documenting the patient encounter, as alternative hypotheses for a medical fact that could be extracted from the text. | 9. An apparatus comprising: at least one processor; and at least one memory storing processor-executable instructions that, when executed by the at least one processor, perform a method of analyzing a text documenting a patient encounter, the method comprising: analyzing the text to identify a set of one or more features of at least a portion of the text; correlating the set of one or more features to a set of alternative hypotheses for an abstract semantic concept representing an intended semantic meaning of the at least a portion of the text; computing, using at least one statistical model implemented using at least one processor and for each of at least some of the alternative hypotheses of the set, one or more measures of estimated likelihood that the respective alternative hypothesis accurately represents the intended semantic meaning of the at least a portion of the text; identifying hypotheses, including some or all of the at least some of the alternative hypotheses, to be presented to a user, wherein identifying the hypotheses comprises, for each of the at least some of the alternative hypotheses of the set: in response to determining that the one or more measures of estimated likelihood for the alternative hypothesis satisfy one or more criteria, identifying that the alternative hypothesis is to be presented to the user; and presenting the identified hypotheses, to the user documenting the patient encounter, as alternative hypotheses for a medical fact that could be extracted from the text. 14. The apparatus of claim 9 , wherein: the identified hypotheses comprise a first hypothesis and a second hypothesis of the at least some of the alternative hypotheses, and the presenting comprises: presenting the first hypothesis to the user; and in response to a selection by the user of the presented first hypothesis, presenting the second hypothesis to the user. | 0.5 |
7,882,045 | 25 | 26 | 25. The computerized method of claim 24 , wherein the probability-based approach is a Bayesian approach. | 25. The computerized method of claim 24 , wherein the probability-based approach is a Bayesian approach. 26. The computerized method of claim 25 , wherein the Bayesian approach is a Naïve Bayesian approach. | 0.5 |
9,384,408 | 6 | 11 | 6. A method of obtaining contextual information for an image published on a digital medium, the method comprising: (a) identifying, by an image recognition engine, an image published on a digital medium; (b) analyzing the image with an image recognition engine to obtain a set of image tags corresponding to the image, wherein each of the image tags is an object identified in the image; (c) identifying, by a text recognition engine, text published proximate to the image on the digital medium; (d) analyzing the text from step (c) to obtain a set of textual tags, wherein each of the textual tags is a subject identified in the text; and (e) matching, by a matching engine, the set of textual tags with the set of image tags to obtain contextual information of the image, wherein the matched textual tags provide additional specificity for identifying objects in the image. | 6. A method of obtaining contextual information for an image published on a digital medium, the method comprising: (a) identifying, by an image recognition engine, an image published on a digital medium; (b) analyzing the image with an image recognition engine to obtain a set of image tags corresponding to the image, wherein each of the image tags is an object identified in the image; (c) identifying, by a text recognition engine, text published proximate to the image on the digital medium; (d) analyzing the text from step (c) to obtain a set of textual tags, wherein each of the textual tags is a subject identified in the text; and (e) matching, by a matching engine, the set of textual tags with the set of image tags to obtain contextual information of the image, wherein the matched textual tags provide additional specificity for identifying objects in the image. 11. The method of claim 6 , wherein the image recognition engine creates at least one tag for the image, and wherein the tag includes the image tag and positional information corresponding to the image tag. | 0.5 |
9,223,560 | 1 | 3 | 1. A method to manage an initial software installation and configuration script, the method comprising: saving, by a plurality of collaboration tools, a new customization associated with the initial software installation and configuration script in an installation and configuration knowledgebase; saving, by the plurality of collaboration tools, a new solution associated with the initial software installation and configuration script in the installation and configuration knowledgebase; associating, through metadata, the saved new customization or the saved new solution with a plurality of environment parameters and a plurality of errors encountered along with a description of why and how the saved new customization or the saved new solution was developed, wherein the description of why and how the saved new customization or the saved new solution was developed is entered via a user input interface and includes a plurality of new situation features, a plurality of error messages, a plurality of associated knowledge, and a new instance of a script; querying, by a search engine or a similarity engine, the installation and configuration knowledgebase for the new customization or the new solution based on a comparison between a criteria provided by an administrator and an index of vocabularies related to the initial installation and configuration script, wherein the index of vocabularies correlate to a plurality of situation descriptions stored in the configuration knowledgebase; and returning, by the search engine or the similarity engine, a search result based on the querying the installation and configuration knowledgebase, wherein the search result identifies a customization or a solution that exactly matches or is a nearest similar match between the criteria provided by the administrator and the index of vocabularies. | 1. A method to manage an initial software installation and configuration script, the method comprising: saving, by a plurality of collaboration tools, a new customization associated with the initial software installation and configuration script in an installation and configuration knowledgebase; saving, by the plurality of collaboration tools, a new solution associated with the initial software installation and configuration script in the installation and configuration knowledgebase; associating, through metadata, the saved new customization or the saved new solution with a plurality of environment parameters and a plurality of errors encountered along with a description of why and how the saved new customization or the saved new solution was developed, wherein the description of why and how the saved new customization or the saved new solution was developed is entered via a user input interface and includes a plurality of new situation features, a plurality of error messages, a plurality of associated knowledge, and a new instance of a script; querying, by a search engine or a similarity engine, the installation and configuration knowledgebase for the new customization or the new solution based on a comparison between a criteria provided by an administrator and an index of vocabularies related to the initial installation and configuration script, wherein the index of vocabularies correlate to a plurality of situation descriptions stored in the configuration knowledgebase; and returning, by the search engine or the similarity engine, a search result based on the querying the installation and configuration knowledgebase, wherein the search result identifies a customization or a solution that exactly matches or is a nearest similar match between the criteria provided by the administrator and the index of vocabularies. 3. The method of claim 1 , wherein the new solution comprises entering an error fixing associated with an encountered error via an administrator input interface. | 0.838353 |
7,752,081 | 11 | 14 | 11. An apparatus comprising: a database for storing reviews, wherein a subset of reviews may be dominated by a subject-owner; a user interface which allows said subject-owner to apply one or more functions to said subset of reviews dominated by said subject-owner in said database; and a processor that selects a review of said reviewed subject from said database responsive to a review request for said reviewed subject from a requesting user and sends said review to said requesting user, wherein sending said review is responsive to said review request and said one or more functions. | 11. An apparatus comprising: a database for storing reviews, wherein a subset of reviews may be dominated by a subject-owner; a user interface which allows said subject-owner to apply one or more functions to said subset of reviews dominated by said subject-owner in said database; and a processor that selects a review of said reviewed subject from said database responsive to a review request for said reviewed subject from a requesting user and sends said review to said requesting user, wherein sending said review is responsive to said review request and said one or more functions. 14. The apparatus as claimed in claim 11 , wherein said review is one of a plurality of selected reviews of said reviewed subject and said plurality of selected reviews includes a second review, and further wherein said one or more functions includes filtering said second review such that said second review is not included in sending said review to said requesting user, and sending said review further comprises sending an indication that said plurality of selected reviews was filtered. | 0.740466 |
8,400,313 | 1 | 5 | 1. An arousal state classification model generating device for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating device characterized by comprising: learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. | 1. An arousal state classification model generating device for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating device characterized by comprising: learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. 5. The arousal state classification model generating device according to claim 1 , further comprising: blink data storage means for storing the blink data of at least one eye of the object person at the time of blinking; feature data extraction means for extracting the first feature data from the blink data acquired from the blink data storage means; first pattern model storage means for storing the first pattern model generated by the blink waveform pattern model generation means; second feature data storage means for storing the second feature data generated by the feature data generation means; and second pattern model storage means for storing the second pattern model generated by the arousal state pattern model generation means. | 0.5 |
9,601,113 | 14 | 16 | 14. A computing device, comprising: at least one verbal input interface; at least one non-verbal input interface being selected from the group of: a kinetic input interface, an inertial input interface, a perceptual input interface, a touch input interface, a graphical user interface, and a sensor input interface; at least one processor in communication with the at least one verbal input interface and the at least one non-verbal input interface, the at least one processor being configured to: receive verbal input using the verbal input interface; receive, concurrently with at least part of the verbal input, at least one secondary input using the at least one non-verbal input interface; identify one or more target objects from the at least one secondary input; recognize text from the received verbal input; generate an interaction object, the interaction object comprising a natural language expression having references to the one or more identified target objects identified from the at least one secondary input, the references being embedded within the recognized text, the generation of the interaction object comprising identification of at least one attribute associated with each of the one or more identified target objects or at least one operation associated with each of the one or more identified target objects; process the interaction object to identify at least one operation to be executed on at least one of the one or more identified target objects; and execute the operation on the at least one of the one or more identified target objects. | 14. A computing device, comprising: at least one verbal input interface; at least one non-verbal input interface being selected from the group of: a kinetic input interface, an inertial input interface, a perceptual input interface, a touch input interface, a graphical user interface, and a sensor input interface; at least one processor in communication with the at least one verbal input interface and the at least one non-verbal input interface, the at least one processor being configured to: receive verbal input using the verbal input interface; receive, concurrently with at least part of the verbal input, at least one secondary input using the at least one non-verbal input interface; identify one or more target objects from the at least one secondary input; recognize text from the received verbal input; generate an interaction object, the interaction object comprising a natural language expression having references to the one or more identified target objects identified from the at least one secondary input, the references being embedded within the recognized text, the generation of the interaction object comprising identification of at least one attribute associated with each of the one or more identified target objects or at least one operation associated with each of the one or more identified target objects; process the interaction object to identify at least one operation to be executed on at least one of the one or more identified target objects; and execute the operation on the at least one of the one or more identified target objects. 16. The computing device of claim 14 , wherein each of the one or more identified target objects is associated with a metaobject defining the associated at least one attribute or at least one operation. | 0.822183 |
8,234,368 | 1 | 3 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for monitoring a plurality of actions associated with at least one communication for lawful intercept purposes; computer code for correlating the actions into a communication flow independent of an address associated with the actions; and computer code for reporting the communication flow to a lawful intercept framework; wherein the computer program product is operable such that the actions are correlated utilizing a unique identifier of a subscriber associated with the actions; wherein the computer program product is operable such that an address utilized to perform each action is determined to be associated with the unique identifier of the subscriber, and the correlation is based on the determination; wherein the computer program product is operable such that at least a portion of the actions are associated with a different address and each of the different addresses is associated with the unique identifier of the subscriber, such that the portions are correlated based on the determination that each address utilized to perform each action is associated with the unique identifier of the subscriber. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for monitoring a plurality of actions associated with at least one communication for lawful intercept purposes; computer code for correlating the actions into a communication flow independent of an address associated with the actions; and computer code for reporting the communication flow to a lawful intercept framework; wherein the computer program product is operable such that the actions are correlated utilizing a unique identifier of a subscriber associated with the actions; wherein the computer program product is operable such that an address utilized to perform each action is determined to be associated with the unique identifier of the subscriber, and the correlation is based on the determination; wherein the computer program product is operable such that at least a portion of the actions are associated with a different address and each of the different addresses is associated with the unique identifier of the subscriber, such that the portions are correlated based on the determination that each address utilized to perform each action is associated with the unique identifier of the subscriber. 3. The computer program product of claim 1 , wherein the actions are invoked by telecommunications service provider application. | 0.57047 |
8,548,915 | 10 | 13 | 10. A data processing system having at least one processor capable of providing an automatic response to a received user input, the system being programmed to automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, calculate for each of a plurality of predefined answerable statements, a match metric denoting a degree to which the partial user input matches the predefined answerable statement; and (b) (1) if the match metric for one of the predefined answerable statements exceeds a first threshold, send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply but the match metric for at least one of the predefined answerable statements exceeds a second threshold, which second threshold is lower than the first threshold, send, to the user's device, information representing the corresponding at least one of the predefined answerable statements. | 10. A data processing system having at least one processor capable of providing an automatic response to a received user input, the system being programmed to automatically: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a full user input representing the entire answerable statement, calculate for each of a plurality of predefined answerable statements, a match metric denoting a degree to which the partial user input matches the predefined answerable statement; and (b) (1) if the match metric for one of the predefined answerable statements exceeds a first threshold, send, to the user's device, information representing a response associated with said one of the predefined answerable statements, and (2) if part (b)(1) does not apply but the match metric for at least one of the predefined answerable statements exceeds a second threshold, which second threshold is lower than the first threshold, send, to the user's device, information representing the corresponding at least one of the predefined answerable statements. 13. The data processing system of claim 10 wherein the system is further programmed, if part (b)(2) applies, in response to receiving, from the user's device, information indicative of a user's acceptance of one of the at least one of the predefined answerable statements in part (b)(2), to automatically send, to the user's device, information representing a response associated with said accepted one of the at least one of the predefined answerable statements. | 0.5 |
8,249,352 | 8 | 13 | 8. A document image processing method comprising; extracting at least one of character row images included in the specified sentence region; recognizing respective characters included in the extracted character row image; interpreting an original sentence character row comprising the recognized characters and generates an interpreted sentence character row; arranging the respective character row images in the sentence region by contracting the respective character row images, the respective character row images each including an image of an original character row, and the generated respective interpreted sentence character rows in a vacant region except a region arranging the respective character row images from the sentence region; and generating a data of an output document arranged with the respective character row images and the respective interpreted sentence character rows in the sentence region, wherein the arranging includes arranging the interpreted sentence character row and the original sentence character row by first aligning the interpreted sentence character row and the original sentence character row, then by correcting a size of the longer of the interpreted sentence character row and the original sentence character row to match the length of the shorter, and then by confining the interpreted sentence character row and the original sentence character row in the sentence region. | 8. A document image processing method comprising; extracting at least one of character row images included in the specified sentence region; recognizing respective characters included in the extracted character row image; interpreting an original sentence character row comprising the recognized characters and generates an interpreted sentence character row; arranging the respective character row images in the sentence region by contracting the respective character row images, the respective character row images each including an image of an original character row, and the generated respective interpreted sentence character rows in a vacant region except a region arranging the respective character row images from the sentence region; and generating a data of an output document arranged with the respective character row images and the respective interpreted sentence character rows in the sentence region, wherein the arranging includes arranging the interpreted sentence character row and the original sentence character row by first aligning the interpreted sentence character row and the original sentence character row, then by correcting a size of the longer of the interpreted sentence character row and the original sentence character row to match the length of the shorter, and then by confining the interpreted sentence character row and the original sentence character row in the sentence region. 13. The document image processing method according to claim 8 , wherein the character row images and the interpreted sentence character rows are respectively collectively arranged with corresponding to a sentence structure including at least one of the original sentence character rows. | 0.763245 |
8,799,280 | 4 | 10 | 4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals. | 4. The process of claim 1 , wherein the process action of personalizing results of the search based on knowledge of the identified site or IO comprises the actions of: maintaining a record of the individuals' search or interaction history in the search engine; and displaying aspects of the individuals' search or interaction history record to the individuals. 10. The process of claim 4 , wherein the process action of displaying aspects of the individuals' search or interaction history record to the individuals comprises an action of taking the individuals directly to the particular site or IO rather than displaying an information link associated therewith. | 0.816748 |
7,873,594 | 1 | 2 | 1. A computer-readable storage medium storing a system analysis program for analyzing an operational form of a network to which a plurality of servers that constitute a multi-layered system are connected, by using a computer, wherein the system analysis program makes the computer execute processing comprising: collecting messages captured by a switch; analyzing contents of the collected messages; determining process types requested by the collected messages and message types indicating whether or not each of the collected messages is a request message or a response message; storing the determined process types and message types in a protocol-log storage unit as a protocol log; upon input of an instruction for generation of a model: identifying at least one process corresponding to each process type, based on at least one correspondence relationship between at least one request message and at least one response message corresponding to each of the process types which are indicated in the protocol log; selecting a set of messages in accordance with a selection criterion based on certainty of existence of caller-called relationships; generating a transaction model which satisfies at least one limiting condition related to the caller-called relationships between the identified processes, based on the selected messages; upon input of an instruction for analysis: extracting, from the protocol-log storage unit, the protocol log corresponding to at least one caller-called relationship indicated by the transaction model; analyzing a processing status of a transaction constituted by a message indicated by the extracted protocol log; and outputting a result of the analyzing; wherein the selecting determines whether, in a processing time span from a request message to a response message corresponding to an identified process executed by a server belonging to a top layer of the multi-layered system, a message corresponding to another identified process in the top layer of the multi-layered system exists or not, and when no message corresponding to another identified process exists, selects the set of messages that includes the request message, the response message corresponding to the identified processes, and all messages in the processing time span corresponding to identified processes executed by servers belonging to lower layers than the tip layer, the top layer being a layer where the request message from a client computer is received, wherein the transaction model has the caller-called relationships and processing times, wherein the limiting condition includes a condition that a processing time span of a caller process includes a processing time span of a called process, and directions of calls between the plurality of the servers, and wherein the generating generates the transaction model based on the selected set of messages, generates one or more patterns of occurrence each indicating a combination of processes which can be called from processes of each process type, calculates a probability of each of the one or more patterns of occurrence, chooses a predetermined number of ones of the one or more patterns of occurrence having higher probabilities, and generates said transaction model based on the chosen ones of the one or more patterns of occurrence. | 1. A computer-readable storage medium storing a system analysis program for analyzing an operational form of a network to which a plurality of servers that constitute a multi-layered system are connected, by using a computer, wherein the system analysis program makes the computer execute processing comprising: collecting messages captured by a switch; analyzing contents of the collected messages; determining process types requested by the collected messages and message types indicating whether or not each of the collected messages is a request message or a response message; storing the determined process types and message types in a protocol-log storage unit as a protocol log; upon input of an instruction for generation of a model: identifying at least one process corresponding to each process type, based on at least one correspondence relationship between at least one request message and at least one response message corresponding to each of the process types which are indicated in the protocol log; selecting a set of messages in accordance with a selection criterion based on certainty of existence of caller-called relationships; generating a transaction model which satisfies at least one limiting condition related to the caller-called relationships between the identified processes, based on the selected messages; upon input of an instruction for analysis: extracting, from the protocol-log storage unit, the protocol log corresponding to at least one caller-called relationship indicated by the transaction model; analyzing a processing status of a transaction constituted by a message indicated by the extracted protocol log; and outputting a result of the analyzing; wherein the selecting determines whether, in a processing time span from a request message to a response message corresponding to an identified process executed by a server belonging to a top layer of the multi-layered system, a message corresponding to another identified process in the top layer of the multi-layered system exists or not, and when no message corresponding to another identified process exists, selects the set of messages that includes the request message, the response message corresponding to the identified processes, and all messages in the processing time span corresponding to identified processes executed by servers belonging to lower layers than the tip layer, the top layer being a layer where the request message from a client computer is received, wherein the transaction model has the caller-called relationships and processing times, wherein the limiting condition includes a condition that a processing time span of a caller process includes a processing time span of a called process, and directions of calls between the plurality of the servers, and wherein the generating generates the transaction model based on the selected set of messages, generates one or more patterns of occurrence each indicating a combination of processes which can be called from processes of each process type, calculates a probability of each of the one or more patterns of occurrence, chooses a predetermined number of ones of the one or more patterns of occurrence having higher probabilities, and generates said transaction model based on the chosen ones of the one or more patterns of occurrence. 2. The computer-readable medium according to claim 1 , wherein the generating calculates a time necessary for performing processing corresponding to each protocol in each of the plurality of servers, based on a time elapsed after occurrence of a request message until occurrence of a response message corresponding to each process type in a transaction, and sets the calculated time in said transaction model. | 0.528802 |
8,302,080 | 1 | 2 | 1. A method for generating test inputs for applying concolic testing in a program, the method comprising: receiving a program; performing a source-to-source transformation of the program; performing interpretation on the program based on a set of test input values; symbolically executing the program; recording a symbolic constraint for each of one or more conditional expressions encountered during execution of the program further comprising; for each variable occurrence in a Boolean control expression, creating a copy of the expression and setting all other variable occurrences in the expression to their concrete values from the execution, thereby generating a set of expressions where each expression in the set has only a single variable occurrence and each subexpression that does not depend on that variable is replaced with its concrete values; and including analyzing a string operation in the program to identify one or more possible execution paths, generating symbolic inputs representing values of variables in each of the conditional expressions as a numeric expression and a string constraint including generating constraints on string values by modeling string operations using finite state transducers (FSTs) and supplying values from the program's execution in place of intractable sub-expressions, analyzing string operations in the program using the FSTs, wherein the FSTs represent library string functions, and resolving control dependencies by recording a stack trace at a beginning of a function call, wherein functions that called the function are to be added to a set of functions to be analyzed; and generating new inputs to drive the program during a subsequent iteration based on results of solving the recorded string constraints. | 1. A method for generating test inputs for applying concolic testing in a program, the method comprising: receiving a program; performing a source-to-source transformation of the program; performing interpretation on the program based on a set of test input values; symbolically executing the program; recording a symbolic constraint for each of one or more conditional expressions encountered during execution of the program further comprising; for each variable occurrence in a Boolean control expression, creating a copy of the expression and setting all other variable occurrences in the expression to their concrete values from the execution, thereby generating a set of expressions where each expression in the set has only a single variable occurrence and each subexpression that does not depend on that variable is replaced with its concrete values; and including analyzing a string operation in the program to identify one or more possible execution paths, generating symbolic inputs representing values of variables in each of the conditional expressions as a numeric expression and a string constraint including generating constraints on string values by modeling string operations using finite state transducers (FSTs) and supplying values from the program's execution in place of intractable sub-expressions, analyzing string operations in the program using the FSTs, wherein the FSTs represent library string functions, and resolving control dependencies by recording a stack trace at a beginning of a function call, wherein functions that called the function are to be added to a set of functions to be analyzed; and generating new inputs to drive the program during a subsequent iteration based on results of solving the recorded string constraints. 2. The method defined in claim 1 wherein the test input values are dynamically generated input strings based on symbolic string constraints and concrete values gathered from executions of the program. | 0.671053 |
7,941,386 | 17 | 18 | 17. An enterprise-wide forensic data-analysis system comprising: a search pack exchange server that provides search packs to one or more external systems or agencies; a nontransitory computer readable storage module having stored thereon a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms packs; a search pack editor module that creates, edits and deletes search packs; an interpreter module that receives the extracted unknown raw data from the data extraction module; determines which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; accesses the plurality of search packs; automatically identifies suspect data from among the extracted unknown raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and compares the extracted data hash value to find identical and similar suspect data features; and a findings repository having stored therein findings reports. | 17. An enterprise-wide forensic data-analysis system comprising: a search pack exchange server that provides search packs to one or more external systems or agencies; a nontransitory computer readable storage module having stored thereon a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms packs; a search pack editor module that creates, edits and deletes search packs; an interpreter module that receives the extracted unknown raw data from the data extraction module; determines which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; accesses the plurality of search packs; automatically identifies suspect data from among the extracted unknown raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and compares the extracted data hash value to find identical and similar suspect data features; and a findings repository having stored therein findings reports. 18. The system of claim 17 , wherein the search pack editor is adapted to permit a first user to create a search pack and a second user, different from the first user, to access and use the search pack created by the first user. | 0.5 |
6,141,641 | 2 | 3 | 2. The method of claim 1 wherein the acoustic model includes a plurality of deep senones, indicative of leaf senones on a senone tree, having ancestor senones, indicative of predecessor senones on the senone trees, and being characterized by at least one parameter, and wherein adjusting the model size comprises: selecting an ancestor senone; identifying a plurality of deep senones which are descendents of the selected ancestor senone; and clustering parameters in the plurality of deep senones. | 2. The method of claim 1 wherein the acoustic model includes a plurality of deep senones, indicative of leaf senones on a senone tree, having ancestor senones, indicative of predecessor senones on the senone trees, and being characterized by at least one parameter, and wherein adjusting the model size comprises: selecting an ancestor senone; identifying a plurality of deep senones which are descendents of the selected ancestor senone; and clustering parameters in the plurality of deep senones. 3. The method of claim 2 wherein identifying a plurality of deep senones comprises: identifying a pair of parameters to be merged corresponding to the plurality of deep senones. | 0.5 |
9,336,553 | 6 | 9 | 6. The method of claim 1 , generating the newsfeed comprises: ordering the plurality of the candidate stories in the newsfeed based at least in part on the ranking. | 6. The method of claim 1 , generating the newsfeed comprises: ordering the plurality of the candidate stories in the newsfeed based at least in part on the ranking. 9. The method of claim 6 , wherein the attribute in common with the lower ranked candidate story comprises a story type. | 0.574468 |
7,644,356 | 9 | 12 | 9. The method of claim 1 , wherein the generating comprises generating relative position constraints preserving relative positions of the graphic elements in each of the candidate relative layouts. | 9. The method of claim 1 , wherein the generating comprises generating relative position constraints preserving relative positions of the graphic elements in each of the candidate relative layouts. 12. The method of claim 9 , wherein the generating of the relative position constraints comprises incorporating specified minimum distances between adjacent graphic elements in the relative position constraints. | 0.5 |
7,970,759 | 1 | 3 | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 3. The computer implemented method of claim 1 wherein the first inference is further related to identifying an unknown side effect of the drug. | 0.892964 |
6,073,135 | 16 | 18 | 16. A computer program product for representing the connectivity of Web pages, the web pages including links between the Web pages, the links and Web pages being identified by names, the computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions that: sort the names of the Web pages in a memory; delta encode the sorted names while periodically storing full names as checkpoints in the memory, each delta encoded name and checkpoint having an assigned unique identification; twice sort a list of pairs of identifications that represent the links between the Web page, each pair of identifications including a first identification and a second identification, first according to the first identification of each pair to produce an inlist, and second according to the second identification of each pair to produce an outlist; store an array of elements in the memory, there being one array element for each Web page, each element including a first pointer to one of the checkpoints, a second pointer to an associated inlist of the Web page, and a third pointer to an associated outlist of the Web page; and index the array by a particular identification to locate connected Web pages. | 16. A computer program product for representing the connectivity of Web pages, the web pages including links between the Web pages, the links and Web pages being identified by names, the computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions that: sort the names of the Web pages in a memory; delta encode the sorted names while periodically storing full names as checkpoints in the memory, each delta encoded name and checkpoint having an assigned unique identification; twice sort a list of pairs of identifications that represent the links between the Web page, each pair of identifications including a first identification and a second identification, first according to the first identification of each pair to produce an inlist, and second according to the second identification of each pair to produce an outlist; store an array of elements in the memory, there being one array element for each Web page, each element including a first pointer to one of the checkpoints, a second pointer to an associated inlist of the Web page, and a third pointer to an associated outlist of the Web page; and index the array by a particular identification to locate connected Web pages. 18. The computer program product of claim 16 wherein each delta encoded name and checkpoint includes a size indicating the number of common bytes in a shared prefix, bytes of the name that are different than the shared prefix, and the assigned unique identification of the Web page. | 0.695464 |
8,805,686 | 14 | 16 | 14. The method of claim 9 , further including applying dynamic programming to scoring the phrases against ordered, non-overlapping sequences of the likely word instances. | 14. The method of claim 9 , further including applying dynamic programming to scoring the phrases against ordered, non-overlapping sequences of the likely word instances. 16. The method of claim 14 , further including eliminating from consideration phrases that start with one or more words not found in the subset of likely word instances. | 0.5 |
9,208,592 | 11 | 12 | 11. A computer-implemented method for providing a display of clusters, comprising: presenting a plurality of cluster spines in a two-dimensional display, wherein each cluster spine comprises a vector of document clusters; positioning a compass over at least a portion of the clusters of one or more of the cluster spines; placing spine labels for at least one of the spines encompassed by the compass around a circumference of the compass; pinning one of the spine labels to the compass at a fixed location; reorienting the compass within the display; and displaying the pinned spine label at the fixed location on the reoriented compass. | 11. A computer-implemented method for providing a display of clusters, comprising: presenting a plurality of cluster spines in a two-dimensional display, wherein each cluster spine comprises a vector of document clusters; positioning a compass over at least a portion of the clusters of one or more of the cluster spines; placing spine labels for at least one of the spines encompassed by the compass around a circumference of the compass; pinning one of the spine labels to the compass at a fixed location; reorienting the compass within the display; and displaying the pinned spine label at the fixed location on the reoriented compass. 12. A method according to claim 11 , further comprising: determining further spine labels for those cluster spines encompassed by the reoriented compass. | 0.745847 |
10,121,211 | 1 | 2 | 1. A method for identifying waste in a process, comprising: receiving, by at least one computer, an image of one or more discarded products from a camera: performing, by the at least one computer, an object recognition process on the received image to identify the one or more discarded products within the image; acquiring, by the at least one computer, metadata relating to the one or more identified discarded products from the received image; recording, by the at least one computer, the metadata; analyzing, by the at least one computer, the metadata with a rules engine; determining, by the at least one computer, an overage amount of product as a function of the acquired metadata; deriving, by the at least one computer, a suggestion for waste reduction based on the determination; and generating, by the at least one computer, a report based on the recorded metadata, wherein the report includes the suggestion for waste reduction. | 1. A method for identifying waste in a process, comprising: receiving, by at least one computer, an image of one or more discarded products from a camera: performing, by the at least one computer, an object recognition process on the received image to identify the one or more discarded products within the image; acquiring, by the at least one computer, metadata relating to the one or more identified discarded products from the received image; recording, by the at least one computer, the metadata; analyzing, by the at least one computer, the metadata with a rules engine; determining, by the at least one computer, an overage amount of product as a function of the acquired metadata; deriving, by the at least one computer, a suggestion for waste reduction based on the determination; and generating, by the at least one computer, a report based on the recorded metadata, wherein the report includes the suggestion for waste reduction. 2. The method of claim 1 , wherein the performing, by the at least one computer, the object recognition process on the received image comprises performing, by the at least one computer, an edge detection process. | 0.808664 |
9,100,722 | 11 | 18 | 11. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the system to perform a method of selecting content items for presentation to a user, the method comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion. | 11. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the system to perform a method of selecting content items for presentation to a user, the method comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion. 18. The medium of claim 11 , wherein at least one of the candidate content items is associated with at least two metadata tags, and wherein selecting at least one of the candidate content items for presentation to the user is performed based on an aggregate of the user exposure scores for the at least two metadata tags associated with the candidate content item. | 0.5 |
7,773,527 | 1 | 5 | 1. A method for sending a document, comprising: receiving the document from a managed service container for transmission to a connection offering platform, wherein the document is based on an offering, wherein the offering is provided by the connection offering platform for an asset managed by the managed service container; retrieving, from a remote registry, a quality of service policy defined for the offering, wherein the remote registry is located on the connection offering platform; enqueuing the document in a queue corresponding to a quality of service defined in the quality of service policy; dequeuing the document according to the quality of service; and transmitting the document via a network to the connection offering platform, wherein the quality of service policy is described in an extensible markup language (XML) document. | 1. A method for sending a document, comprising: receiving the document from a managed service container for transmission to a connection offering platform, wherein the document is based on an offering, wherein the offering is provided by the connection offering platform for an asset managed by the managed service container; retrieving, from a remote registry, a quality of service policy defined for the offering, wherein the remote registry is located on the connection offering platform; enqueuing the document in a queue corresponding to a quality of service defined in the quality of service policy; dequeuing the document according to the quality of service; and transmitting the document via a network to the connection offering platform, wherein the quality of service policy is described in an extensible markup language (XML) document. 5. The method of claim 1 , further comprising retaining the document after transmission to the connection offering platform in accordance with the quality of service policy. | 0.584135 |
9,280,766 | 1 | 2 | 1. A system for determining EDI rules to enforce, comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: determine entity-specific rules from corresponding companion guides for each of a plurality of entities; express each entity-specific rule in a neutral and machine readable format; classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, or whether the entity-specific rule is unique; convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities. | 1. A system for determining EDI rules to enforce, comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: determine entity-specific rules from corresponding companion guides for each of a plurality of entities; express each entity-specific rule in a neutral and machine readable format; classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, or whether the entity-specific rule is unique; convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities. 2. The system of claim 1 , wherein the memory further stores computer usable program code executed by the processor to: determine a first current rule set for a first one of the plurality of entities comprising at least one of the entity-specific rules; and validate a first EDI document associated with the first one of the plurality of entities by: comparing the first EDI document to the first current rule set; forwarding the first EDI document to the first one of the plurality of entities if the EDI document matches the first current rule set, wherein the EDI document is validated; and returning the first EDI document to a sender if the first EDI document does not match the first current rule set, wherein the first EDI document is invalidated. | 0.5 |
7,548,895 | 7 | 18 | 7. The computer-implemented system of claim 1 further comprising: an action manager component that receives a candidate task directly or indirectly from the task component and prompts a user about the candidate task. | 7. The computer-implemented system of claim 1 further comprising: an action manager component that receives a candidate task directly or indirectly from the task component and prompts a user about the candidate task. 18. The computer-implemented system of claim 7 , the action manager component contacts a user subsequent to a completion of communications via a similar communication means utilized for the communications to prompt for a follow up to the candidate task. | 0.5 |
8,316,021 | 1 | 2 | 1. A web-based computer search engine system for receiving a search query from a user at a remote computer and returning a search results webpage, the system comprising: an input for receiving the search query from the user displayable on the remote computer; a processor for processing the search query and for causing the results webpage to be transmitted to the remote computer in response to the search query, the results webpage including respective links to, and respective website information relating to the content of, websites responsive to the search query; a non-transitory computer-readable recording medium for storing the website information; and a feedback input displayable on the remote computer and adapted to receive a first feedback from the user relating to a perceived relevance of the website information included in the search results webpage relative to the search query, and further adapted to receive a second feedback from the user relating to a perceived relevance of at least one of the websites visited by the user relative to the search query, the second user feedback received after the user visits the at least one of the websites, wherein the processor is adapted to receive the first and second feedbacks and is further adapted to amend the website information at least in part based on the first and second feedbacks. | 1. A web-based computer search engine system for receiving a search query from a user at a remote computer and returning a search results webpage, the system comprising: an input for receiving the search query from the user displayable on the remote computer; a processor for processing the search query and for causing the results webpage to be transmitted to the remote computer in response to the search query, the results webpage including respective links to, and respective website information relating to the content of, websites responsive to the search query; a non-transitory computer-readable recording medium for storing the website information; and a feedback input displayable on the remote computer and adapted to receive a first feedback from the user relating to a perceived relevance of the website information included in the search results webpage relative to the search query, and further adapted to receive a second feedback from the user relating to a perceived relevance of at least one of the websites visited by the user relative to the search query, the second user feedback received after the user visits the at least one of the websites, wherein the processor is adapted to receive the first and second feedbacks and is further adapted to amend the website information at least in part based on the first and second feedbacks. 2. The system of claim 1 , wherein the computer readable recording medium includes information relating to whether the user has provided a minimum number of first and second feedbacks; and the first and second feedbacks analyzed by the processor when amending the website information include only the first and second feedbacks for the users that have completed the minimum number of entries. | 0.5 |
9,779,140 | 12 | 14 | 12. The system according to claim 11 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. | 12. The system according to claim 11 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. 14. The system according to claim 12 , wherein the network device is further operable to: weigh the second score signal, if one or both of: the at least one web page search result comprises one or more music-related terms; or the at least one web page search result comprises a music-related web page. | 0.5 |
7,752,195 | 19 | 21 | 19. The computer system of claim 18 , further comprising: continuing to add identification of items to the universal query result set based on determined probabilities until a predetermined number of items have been listed. | 19. The computer system of claim 18 , further comprising: continuing to add identification of items to the universal query result set based on determined probabilities until a predetermined number of items have been listed. 21. The computer system of claim 19 , further comprising: tracking a result of the transmitted universal query result set; and storing the tracked result and the query as a historical query. | 0.543269 |
8,700,378 | 9 | 10 | 9. A computer-implemented method for propagating symbolic expressions, the method comprising: identifying a graphical model by a computer, wherein the graphical model comprises a first entity coupled to a second entity and connectivity information, wherein the first entity comprises a first property, a first behavioral constraint, and optionally a first behavioral description, wherein the second entity comprises the first property, a second behavioral constraint, and optionally a second behavioral description, wherein the first behavioral constraint and the second behavioral constraint are identical or different, wherein the first behavioral description and the second behavioral description are identical or different; receiving by the computer a first symbolic expression to represent the first property of the first entity in the graphical model; identifying by the computer the first property in the first entity and the first property in the second entity based on at least one of the connectivity information, a behavioral constraint of the first entity or the second entity, or a behavioral description of the first entity or the second entity; propagating by the computer the first symbolic expression to the second entity to represent the first property of the second entity with the first symbolic expression; expressing by the computer the first and the second entities in terms of the first symbolic expression to obtain an updated graphical model; identifying an under-specified constraint between the first symbolic expression and a second symbolic expression, when the first symbolic expression and the second symbolic expression do not inherently conflict but at least one entity of the graphical model is unable to be expressed in terms of the first symbolic expression or the second symbolic expression; generating a constraint between the first symbolic expression and the second symbolic expression when an under-specified constraint exists, wherein the generated constraint is consistent with the graphical model; and displaying by the computer the updated graphical model. | 9. A computer-implemented method for propagating symbolic expressions, the method comprising: identifying a graphical model by a computer, wherein the graphical model comprises a first entity coupled to a second entity and connectivity information, wherein the first entity comprises a first property, a first behavioral constraint, and optionally a first behavioral description, wherein the second entity comprises the first property, a second behavioral constraint, and optionally a second behavioral description, wherein the first behavioral constraint and the second behavioral constraint are identical or different, wherein the first behavioral description and the second behavioral description are identical or different; receiving by the computer a first symbolic expression to represent the first property of the first entity in the graphical model; identifying by the computer the first property in the first entity and the first property in the second entity based on at least one of the connectivity information, a behavioral constraint of the first entity or the second entity, or a behavioral description of the first entity or the second entity; propagating by the computer the first symbolic expression to the second entity to represent the first property of the second entity with the first symbolic expression; expressing by the computer the first and the second entities in terms of the first symbolic expression to obtain an updated graphical model; identifying an under-specified constraint between the first symbolic expression and a second symbolic expression, when the first symbolic expression and the second symbolic expression do not inherently conflict but at least one entity of the graphical model is unable to be expressed in terms of the first symbolic expression or the second symbolic expression; generating a constraint between the first symbolic expression and the second symbolic expression when an under-specified constraint exists, wherein the generated constraint is consistent with the graphical model; and displaying by the computer the updated graphical model. 10. The method of claim 9 , further comprising: generating a reconfigurable code based on the graphical model and the first symbolic expression. | 0.941982 |
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