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METHOD, DEVICE, COMPUTER PROGRAM AND COMPUTER READABLE RECORDING MEDIUM FOR DETERMINING OPINION SPAM BASED ON FRAME

Thu, 27 Oct 2016 08:00:00 EDT

A frame-based opinion spam determination method is provided. The method is performed by a processor of a frame-based opinion spam determination device. The method may include (a) receiving an input text; and (b) determining whether or not the input text is opinion spam using a machine learning-based opinion spam determination model considering a frame extracted from multiple opinion spam samples as an opinion spam determination element, wherein the frame is a semantic unit of included in an event expressed in a sentence.



ACTION ANALYSIS SERVER, METHOD OF ANALYZING ACTION, AND PROGRAM FOR ACTION ANALYSIS SERVER

Thu, 27 Oct 2016 08:00:00 EDT

The present invention is to provide an action analysis server learning the action of the user wearing a wearable terminal and informing a manager that a problem is occurred when the user takes any action other than the learned actions. The action analysis server 10 communicatively connected with the wearable terminal 100 worn by a user, regularly receives location data showing the user's current location, or acceleration data sensed by the wearable terminal 100 as action data from the wearable terminal 100, learns the user's action at the received time frame based on the received action data and generates a learning record, and executes an alert process when receiving action data not matched with the learning record from the wearable terminal.



AUTOMATED DEFECT AND OPTIMIZATION DISCOVERY

Thu, 27 Oct 2016 08:00:00 EDT

Performance information and configuration information is received for the plurality of computer systems. The computer systems are grouped into a plurality of clusters based at least in part on the performance information, where the plurality of clusters includes a first cluster and a second cluster. A system configuration associated with the first cluster is automatically identified from the configuration information and is automatically sent to the second cluster.



CLASSIFICATION OF HIGHLY-SKEWED DATA

Thu, 27 Oct 2016 08:00:00 EDT

A method for identifying highly-skewed classes using an imperfect annotation of every instance together with a set of features for all instances. The imperfect annotations designate a plurality of instances as belonging to the target rare class and others to the majority class. First, a classifier is trained on the set of features using the imperfect annotation as supervision, to designate each instance to either the rare class or majority class. A combination of the predictions from the trained classifier and the imperfect annotations is then used to classify each instance to either the rare class or majority class. In particular, an instance is classified to the rare class only when both the trained classifier and the imperfect annotation classify the instance to the rare class. Finally, for each instance assigned as a rare class instance by the combination stage, all instances in its neighborhood are re-classified as either rare class or majority class.



SYSTEMS AND METHODS FOR IMPROVING ACCURACY IN MEDIA ASSET RECOMMENDATIONS BASED ON DATA FROM ONE DATA SPACE

Thu, 27 Oct 2016 08:00:00 EDT

Methods and systems are described for processing media consumption information across a data space with different types of user preference information. User preference information is received in a form of a data space. User preference information includes both monitored user interactions with respect to media assets and levels of enjoyment that users expressly input with respect to the media assets. Both types of preference information are transformed to consumption layer preference information and attributes indicative of users' preferences are determined. An estimated explicit user preference and an estimated implicit user preference are determined. The two estimated user preference values are compared and an error value is calculated based on the comparison.



METHOD AND SYSTEM FOR REAL TIME PRODUCTION OPTIMIZATION BASED ON EQUIPMENT LIFE

Thu, 27 Oct 2016 08:00:00 EDT

A system and method include a controlled mechanical system coupled to self-optimization of equipment life system. The method includes providing a controlled mechanical system; collecting and aggregating data in a time series related to the controlled mechanical system for processing with a monitoring module; calculating an estimated current level of degradation of the controlled mechanical system from the collected and aggregated data with a learning and prognostic module; determining, with the learning and prognostic module, trade-offs between degradation and performance of the controlled mechanical system for the next optimization period; and calculating an optimum operating point for the controlled mechanical system based on the forecast and economic data with an optimization module. Numerous other aspects are provided.



LEVERAGING LEARNED PROGRAMS FOR DATA MANIPULATION

Thu, 27 Oct 2016 08:00:00 EDT

Examples of the present disclosure describe leveraging of learned programs for data manipulation. A template associated with information including non-marked up content is detected by applying machine learning processing that compares the information with a plurality of stored templates. The learned program is detected from a learned program pool comprising a plurality of learned programs based on the template detected. Extracted data from the information is manipulated based on application of the learned program. Other examples are also described.



METHOD OF MAINTENANCE OF EQUIPMENT

Thu, 27 Oct 2016 08:00:00 EDT

The invention relates to a method for maintaining equipment likely to go through at least a degraded state before failing, this equipment being provided with a data sensor, linked to a recorder, which is in turn associated with a processing unit, which comprises the following steps of: detection of states of the equipment from the recorded data, and by means of a hidden Markov model, determination of an optimal maintenance date as a function of a state of the equipment, of a predetermined aggregate usage time of the equipment, by using an optimal stop on PDMP, which comprises: a substep of calculation of a quantization grid made up of cells with, for each cell, the transition date, the state of the equipment on that transition date, the time spent in the preceding state, the probability of being in said state on said date, a substep of calculation of a discretized grid of remaining usage time for each cell of the quantization grid, a substep of calculation of the maintenance date starting from a state of the equipment detected on a date t and from the date of transition into this state which is itself determined as a function of the usage time, and by using the discretized quantization grid. The so-called optimal maintenance date is determined by minimizing the mathematical expectation of an hourly cost function; there is also associated with each cell of the discretized quantization grid a probability of going from the state of said cell to each other possible state.



SYSTEMS AND METHODS FOR IMPROVING ACCURACY IN MEDIA ASSET RECOMMENDATIONS BASED ON DATA FROM MULTIPLE DATA SPACES

Thu, 27 Oct 2016 08:00:00 EDT

Methods and systems are described for processing media consumption information across multiple data spaces over a common media asset space. User preference information is received from two data spaces. User preference information from the first data space includes monitored user interactions of a first plurality of users with respect to a first plurality of media assets and user preference information from the second data space includes levels of enjoyment that a second plurality of users expressly input with respect to a second plurality of media assets. Both sets of preference information are transformed to respective consumption layer preference information and respective attributes indicative of users' preferences are determined. A first and second sentimental similarity values are determined for the first and second preference information respectively. The two sentimental similarity values are compared and an error value is calculated based on the comparison.



METHOD OF INTUITION GENERATION

Thu, 27 Oct 2016 08:00:00 EDT

An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.



DECISION PROCESSING AND INFORMATION SHARING IN DISTRIBUTED COMPUTING ENVIRONMENT

Thu, 27 Oct 2016 08:00:00 EDT

A request arrival rate is obtained at a given computing node in a computing network comprising a plurality of distributed computing nodes. A topology of the computing network is determined at the given computing node so as to identify neighboring computing nodes with respect to the given computing node. A probability is computed at the given computing node based on the obtained request arrival rate and the detected network topology. The computed probability is used to select a decision from a set of decision candidates in response to a request received at the given computing node in a given time slot. The selected decision is a decision with a top average reward attributed thereto across the given computing node and the neighboring computing nodes determined based on information shared by the neighboring computing node with the given computing node.



INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, PROGRAM, AND INFORMATION PROCESSING SYSTEM

Thu, 27 Oct 2016 08:00:00 EDT

Provided is an information processing apparatus including: a status recognition unit configured to recognize a status of a reference apparatus on the basis of information on a status of an apparatus corresponding to the reference apparatus, the reference apparatus serving as a reference when a behavior recognition mode for deciding a status of behavior is set; and a behavior-recognition-mode setting unit configured to set the behavior recognition mode for a setting target apparatus for which the behavior recognition mode is to be set on the basis of the recognized status of the reference apparatus.



PREDICTION OF A CURTAILED CONSUMPTION OF FLUID

Thu, 27 Oct 2016 08:00:00 EDT

A computing system for predicting a curtailed consumption of fluid comprising: a module for collecting consumption data comprising information relating to an actual consumption of fluid of a plurality of consumers during a learning phase, a processing circuit for aggregating the consumption data collected by groups as a function of at least one determined descriptive variable associated with each consumer and contained in the consumption data, a processor for determining on the basis of the aggregated consumption data a curve of global load for each group, a computer for computing a model of extraction of a load curve, termed heating and/or air conditioning, on the basis of each global load curve and of meteorological data, and a predictor for computing a prediction of a curtailed consumption of fluid for each group during a forthcoming curtailment phase.



METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR DETERMINING A PROVIDER RETURN RATE

Thu, 27 Oct 2016 08:00:00 EDT

Provided herein are systems, methods and computer readable media for classifying a provider of products, services or experiences as a provider that should be engaged based on a predicted return rate for any products, services or experiences that may be offered and purchased by a consumer. An example method may comprise supplying a classifying model with a dataset, wherein the dataset comprises an identification of a provider and a plurality of attributes corresponding to the provider and identifying a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model.



Attitude Detection

Thu, 27 Oct 2016 08:00:00 EDT

Embodiments relate to detecting an attitude of a user towards a target prior to or without presence of a direct expression of the attitude. A dictionary is built with a first collection of positive attitude content and a second collection of negative attitude content. In addition, a statistical model of attitude relevance is constructed based on content based similarity metrics. The model utilizes the dictionary and statistically assesses attitude relevance. Based on the assessment the user is classified as relevant or non-relevant for attitude towards the target.



Attitude Detection

Thu, 27 Oct 2016 08:00:00 EDT

Embodiments relate to detecting an attitude of a user towards a target prior to or without presence of a direct expression of the attitude. A dictionary is built with a first collection of positive attitude content and a second collection of negative attitude content. In addition, a statistical model of attitude relevance is constructed based on content based similarity metrics. The model utilizes the dictionary and statistically assesses attitude relevance. Based on the assessment the user is classified as relevant or non-relevant for attitude towards the target.



RECURSIVE ADAPTIVE INTERACTION MANAGEMENT SYSTEM

Thu, 27 Oct 2016 08:00:00 EDT

A management system for guiding an agent in a media-specific dialogue has a conversion engine for instantiating ongoing dialogue as machine-readable text, if the dialogue is in voice media, a context analysis engine for determining facts from the text, a rules engine for asserting rules based on fact input, and a presentation engine for presenting information to the agent to guide the agent in the dialogue. The context analysis engine passes determined facts to the rules engine, which selects and asserts to the presentation engine rules based on the facts, and the presentation engine provides periodically updated guidance to the agent based on the rules asserted.



SYSTEM FOR DERIVING DATA IN CONSTRAINED ENVIRONMENTS

Thu, 27 Oct 2016 08:00:00 EDT

A system and approach for deriving data for a constrained environment of a controller such as, for example, an embedded device. The controller may incorporate a processor and a memory connected to the processor. The memory may have a constrained capacity. The memory may contain an extensible set of rules for deriving additional semantic information from available information at the embedded device. The processor and the memory with the extensible set of rules may constitute a semantic rule engine. The semantic rule engine may apply the extensible set of rules to the available information to derive the additional semantic information.



METHOD AND DEVICE FOR CONSTRUCTING EVENT KNOWLEDGE BASE

Thu, 27 Oct 2016 08:00:00 EDT

Proposed are a method and device for constructing an event knowledge. The method comprises: identifying text to obtain an event mining candidate sentence; dividing the event mining candidate sentence into syntax fragments; generating an event knowledge instance according to the syntax fragments and a preset event knowledge construction, in which the number of the event knowledge instances is equal to the number of verb-object fragments and subject-predicate fragments in the syntax fragments; obtaining an event mining target sentence according to the verb-object fragments and the subject-predicate fragments in the syntax fragments, dividing the event mining target sentence, and writing divided members into an event knowledge instance correspondingly, so as to accomplish construction of the event knowledge base.



Clarification of Submitted Questions in a Question and Answer System

Thu, 27 Oct 2016 08:00:00 EDT

Mechanisms for clarifying an input question are provided. A question is received for generation of an answer. A set of candidate answers is generated based on an analysis of a corpus of information. Each candidate answer has an evidence passage supporting the candidate answer. Based on the set of candidate answers, a determination is made as to whether clarification of the question is required. In response to a determination that clarification of the question is required, a request is sent for user input to clarify the question. User input is received from the computing device in response to the request and at least one candidate answer in the set of candidate answers is selected as an answer for the question based on the user input.



GENERATING USING A BIDIRECTIONAL RNN VARIATIONS TO MUSIC

Thu, 27 Oct 2016 08:00:00 EDT

Methods and apparatus, including computer program products, are provided for receiving, at a bidirectional recurrent neural network, a music file preprocessed to include at least one token data inserted within at least one location in the music file in order to enable varying the music file; generating, by the bidirectional recurrent neural network, an output music file, wherein the bidirectional recurrent neural network generates music data to replace the at least one token data; and providing, by the bidirectional recurrent neural network, the output music file representing a varied version of the music file. Related apparatus, systems, methods, and articles are also described.



PREDICTIVE MODELING OF RESPIRATORY DISEASE RISK AND EVENTS

Thu, 27 Oct 2016 08:00:00 EDT

An application server predicts respiratory disease risk, rescue medication usage, exacerbation, and healthcare utilization using trained predictive models. The application server includes model modules and submodel modules, which communicate with a database server, data sources, and client devices. The submodel modules train submodels by determining submodel coefficients based on training data from the database server. The submodel modules further determine statistical analysis data and estimates for medication usage events, healthcare utilization, and other related events. The model modules combine submodels to predict respiratory disease risk, exacerbation, rescue medication usage, healthcare utilization, and other related information. Model outputs are provided to users, including patients, providers, healthcare companies, electronic health record systems, real estate companies and other interested parties.



ENVIRONMENTAL SENSOR-BASED COGNITIVE ASSESSMENT

Thu, 27 Oct 2016 08:00:00 EDT

Methods, systems, and techniques for facilitating cognitive assessment are provided. Example embodiments provide a Cognitive Assessment Facilitator System CAFS, which facilitates the gathering and prediction of cognitive assessment of individuals using machine learning and sensors placed in the home of a resident. These predictive assessments can then be used by a clinician to further diagnose and/or provide health intervention. In one embodiment, the CAFS comprises a sensor input module, a machine learning engine (or algorithm as part of another component), a CAAB tool, and activity curve change engine (activity tools), and a reporting module 308. These components cooperate to process and transform smart home based sensor data into activity performance features and statistical activity features which are then processing through a machine learning engine to predict clinical cognitive assessment values.



DEVICE, SYSTEM AND METHOD FOR ASSESSING RISK OF VARIANT-SPECIFIC GENE DYSFUNCTION

Thu, 27 Oct 2016 08:00:00 EDT

A device, system and method for predicting gene-dysfunction caused by a genetic mutation in the genome of an organism. A neural network may comprise multiple nodes respectively associated with multiple different gene-dysfunction metrics and multiple different confidence weights. The neural network may combine the multiple gene-dysfunction metrics according to the respective associated confidence weights to generate one or more likelihoods that a genetic mutation causes gene-dysfunction in organisms. In a training-phase, the neural network may be trained using an input data set including genetic mutations to generate new gene-dysfunction metrics and new associated confidence weights that optimize the neural network based on a cost factor. In a run-time phase, a genetic mutation may be identified and one or more likelihoods may be computed that the identified genetic mutation causes gene-dysfunction in the organism based on the new gene-dysfunction metrics and the associated new confidence weights of the neural network.



SYSTEMS AND METHODS FOR PREDICTING A SMOKING STATUS OF AN INDIVIDUAL

Thu, 27 Oct 2016 08:00:00 EDT

Systems and methods are provided for assessing a sample obtained from a subject. The computerized method includes receiving, by receiving circuitry, a dataset associated with the sample, the dataset comprising quantitative expression data for LRRN3, CDKN1C, PALLD, SASH1, RGL1, and TNFRSF17. A processor generates, based on the received dataset, a score that is indicative of a predicted smoking status of the subject. The predicted smoking status may classify the subject as a current smoker or as a non-current smoker.



BIOLOGICAL STATE-EVALUATING APPARATUS, BIOLOGICAL STATE-EVALUATING METHOD, BIOLOGICAL STATE-EVALUATING SYSTEM, BIOLOGICAL STATE-EVALUATING PROGRAM, EVALUATION FUNCTION-GENERATING APPARATUS, EVALUATION FUNCTION-GENERATING METHOD, EVALUATION FUNCTION-GENERATING PROGRAM AND RECORDING MEDIUM

Thu, 27 Oct 2016 08:00:00 EDT

A biological state-evaluating apparatus evaluates the biological state to be evaluated, based on generated evaluation function and the previously acquired metabolite concentration data to be evaluated. In the apparatus, a candidate evaluation function-generating unit generates a candidate evaluation function that is a candidate of the evaluation function from the biological state information according to a particular function-generating method. A candidate evaluation function-verifying unit verifies the candidate evaluation function prepared according to a particular verification method. A variable-selecting unit selects the combination of the metabolite concentration data contained in the biological state information to be used in preparing the candidate evaluation function by selecting a variable of the candidate evaluation function from the verification results according to a particular variable selection method. The apparatus generates the evaluation function by selecting a candidate evaluation function to be used as the evaluation function among the candidate evaluation functions based on the verification results accumulated by repeated execution of those units.



GAPLESS MEDIA GENERATION

Thu, 27 Oct 2016 08:00:00 EDT

A media engine may determine if a received media file is according to a format that includes metadata indicating gap information such as in the header of the file container. If metadata indicating gap information is detected that information may be provided to the media engine by a media file parser and used by the media engine to create a media stream with gap(s) removed based on the metadata. If the received media file does not include metadata indicating gap information, heuristics may be employed to estimate and remove gap(s) in the resulting media stream. The media stream may then be saved or played.



YIELD ESTIMATION AND CONTROL

Thu, 27 Oct 2016 08:00:00 EDT

A defect prediction method for a device manufacturing process involving production substrates processed by a lithographic apparatus, the method including training a classification model using a training set including measured or determined values of a process parameter associated with the production substrates processed by the device manufacturing process and an indication regarding existence of defects associated with the production substrates processed in the device manufacturing process under the values of the process parameter, and producing an output from the classification model that indicates a prediction of a defect for a substrate.



INFERRING CONTRIBUTIONS OF CONTENT TO SALES EVENTS

Thu, 20 Oct 2016 08:00:00 EDT

Disclosed in some examples are systems, methods, and machine readable mediums that infer contributions from content distributed on a hierarchical electronic content distribution system to the occurrence of events using observed interactions related to the content. For example, the system may infer that a particular item of content that was shared through the hierarchical electronic content distribution system caused a person to apply to the company seeking to be hired. As another example, the system may infer that a particular item of shared content caused or contributed to a sale of the company's products. As yet another example, the system may infer that a particular item of shared content caused or contributed to an increase in a metric associated with the organization.



METHOD FOR PROCESSING INFORMATION BY INTELLIGENT AGENT AND INTELLIGENT AGENT

Thu, 20 Oct 2016 08:00:00 EDT

A method for processing information by an intelligent agent and the intelligent agent, where the method comprises: a first intelligent agent sends a request message to a second intelligent agent, where the request message includes an invitation message or a recommendation message; the first intelligent agent receives a decision message fed back by the second intelligent agent, where the decision message is determined according to the invitation message or the recommendation message and a knowledge model of the second intelligent agent; and the first intelligent agent updates, according to the decision message, a knowledge model of the first intelligent agent or sends a notification message to a first user account corresponding to the first intelligent agent. By using these technical solutions, information on a social network may be learned and processed by means of interaction with another intelligent agent, thereby implementing mining of data on the social network.



SYSTEM AND METHOD FOR LEARNING AND/OR OPTIMIZING MANUFACTURING PROCESSES

Thu, 20 Oct 2016 08:00:00 EDT

A system and method for learning and/or optimizing processes related to semiconductor manufacturing is provided. A learning component generates a set of candidate process models based on process data associated with one or more fabrication tools. The learning component also selects a particular process model from the set of candidate process models that is associated with lowest error. An optimization component generates a set of candidate solutions associated with the particular process model. The optimization component also selects a particular solution from the set of candidate solutions based on a target output value and an output value associated with the particular solution.



METHOD AND APPARATUS FOR ACQUIRING TRAINING PARAMETERS FOR A MODEL

Thu, 20 Oct 2016 08:00:00 EDT

Method and device of selecting training parameters for training a model are disclosed. The method includes: (1) setting a precision requirement for the model, and a first parameter value interval defined by an upper limit and a lower limit; (2) obtaining a first value point and a second value point within the first parameter value interval; (3) obtaining and comparing respective first and second error rates by respectively setting the training parameter at the first and second value points for the model; (4) updating three values out of the upper limit, the lower limit, the first value point and the second value point; (5) repeating steps (3) and (4), until the precision requirement is net by the respective first and second value points; and (6) obtaining the optimal value of the training parameter.



PERFORMING SENTIMENT ANALYSIS

Thu, 20 Oct 2016 08:00:00 EDT

There is provided a computer-implemented method of performing sentiment analysis. An exemplary method comprises performing a first sentiment analysis on microblogging data based on a method using an opinion lexicon. The method also includes training a classifier using training data from the first sentiment analysis. Additionally, the method includes identifying a new opinion term in the microblogging data by performing a statistical test. The new opinion terms are not in the opinion lexicon. The method also includes identifying new microblogging data based on the new opinion term. Further, the method includes performing a second sentiment analysis on the new microblogging data using the classifier.



LARGE-SCALE BATCH ACTIVE LEARNING USING LOCALITY SENSITIVE HASHING

Thu, 20 Oct 2016 08:00:00 EDT

A system and method for selection of a batch of objects are provided. Each object in a pool is assigned to a subset of a set of buckets. The assignment is based on signatures, generated, for example, by LSH hashing object representations of the objects in the pool. The signatures are then segmented into bands which are each assigned to a respective bucket in the set, based on the elements of the band. An entropy value is computed for each of a set of objects remaining in the pool using a current classifier model. A batch of objects for retraining the model is selected. This includes selecting objects from the set of objects based on their computed entropy values and respective assigned buckets.



SYSTEM AND METHOD FOR OPTIMIZING TEAMS

Thu, 20 Oct 2016 08:00:00 EDT

A system, method and program product for optimizing a team to solve a problem. The system includes: a team building system for building a fundamental analytic team from a database of analysts to solve an inputted problem, wherein the fundamental analytic team includes at least one cluster of analysts characterized with specificity and at least one cluster of analysts characterized with sensitivity; and a problem analysis system that collects sensor data from the fundamental analytic team operating within an immersive environment, wherein the problem analysis system includes a system for evaluating the sensor data to identify a bias condition from the fundamental analytic team, and includes a system for altering variables in the immersive environment in response to a detected bias condition.



ARCHIVING SYSTEMS AND METHODS USING MESSAGE CATEGORIZATION AND CLASSIFICATION PROCESSES

Thu, 20 Oct 2016 08:00:00 EDT

A method is presented for archiving messages, the method including receiving a plurality of messages from a plurality of computing devices via a network, analyzing each of the plurality of messages, creating a full text index for each of the plurality of messages, executing a probabilistic classifier, comparing the full text index of each of the plurality of messages to a plurality of classifications, applying a tag classifier to each message of the plurality of messages based on an identified classification from the plurality of classifications and categorizing each tag classifier into one or more of a plurality of categories.



QUESTIONABLE FACT CHECKING METHOD AND SYSTEM

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



EFFICIENT FACT CHECKING METHOD AND SYSTEM UTILIZING SOURCES ON DEVICES OF DIFFERING SPEEDS

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



REVERSE FACT CHECKING METHOD AND SYSTEM

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



EFFICIENT FACT CHECKING METHOD AND SYSTEM UTILIZING CONTROLLED BROADENING SOURCES

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



RANDOM FACT CHECKING METHOD AND SYSTEM

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



FACT CHECKING BY SEPARATION METHOD AND SYSTEM

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



FOCUSED FACT CHECKING METHOD AND SYSTEM

Thu, 20 Oct 2016 08:00:00 EDT

An efficient fact checking system analyzes and determines the factual accuracy of information and/or characterizes the information by comparing the information with source information. The efficient fact checking system automatically monitors information, processes the information, fact checks the information efficiently and/or provides a status of the information.



METHOD, DEVICE, AND SERVER FOR FRIEND RECOMMENDATION

Thu, 20 Oct 2016 08:00:00 EDT

Methods, devices, and servers for friend recommendation are provided. A user association set of a target user is obtained. Original data of each associated user in the user association set is obtained. The original data include location relationship data, associated friend data, time relationship data, or combinations thereof, between each associated user and the target user. The original data of each associated user is screened to obtain feature data to form a feature collection for each associated user. A pre-configured N-Tree prediction model is used to process the feature collection for a prediction calculation to obtain an association-predicting value for each associated user. According to the association-predicting value of each associated user, a friend user for the target user from the user association set is determined and recommended to the target user.



SYSTEMS AND METHODS FOR INTELLIGENT ALERT FILTERS

Thu, 20 Oct 2016 08:00:00 EDT

A system and method of generating intelligent alerts based on updatable rules, filters, or algorithms, the method includes receiving one or more device status messages from sensors monitoring devices of a monitored system, determining an alert priority for each of the one or more device status messages, storing the alert priority, the respective device status message, and associated metadata in a data store, providing an alert message to an interactive user interface, the alert message indicating the alert priority, monitoring a user's interaction with the alert message, classifying the user's interaction with the alert message, storing the user's interaction correlated with the corresponding alert message in a data store, analyzing the user's interaction to develop correlations between a cause of respective device status message, its associated data, and the user's interaction, and updating a data store with the correlation. A system and non-transitory computer readable medium are also disclosed.



NORMALIZATION OF PREDICTIVE MODEL SCORES

Thu, 20 Oct 2016 08:00:00 EDT

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for score normalization. One of the methods includes receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output. The method includes generating a first trained predictive model using the initial training data and a training function. The method includes generating intermediate training records by inputting input data of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function, each intermediate training record having a score. The method also includes generating a score normalization model using a score normalization training function and the intermediate training records.



ANNEALED DROPOUT TRAINING OF NEURAL NETWORKS

Thu, 20 Oct 2016 08:00:00 EDT

Systems and methods for training a neural network to optimize network performance, including sampling an applied dropout rate for one or more nodes of the network to evaluate a current generalization performance of one or more training models. An optimized annealing schedule may be generated based on the sampling, wherein the optimized annealing schedule includes an altered dropout rate configured to improve a generalization performance of the network. A number of nodes of the network may be adjusted in accordance with a dropout rate specified in the optimized annealing schedule. The steps may then be iterated until the generalization performance of the network is maximized.



Method and Apparatus for Automatically Replying to Information

Thu, 20 Oct 2016 08:00:00 EDT

The present disclosure includes acquiring a keyword of information to be replied to, as a first feature, and acquiring a keyword of a pending reply in a pending reply set as a second feature, calculating, according to a correlation between the first feature and the second feature, a match between the information to be replied to and the pending reply, where the correlation between the first feature and the second feature is obtained through multiple trainings according to an original text and a reply to the original text that are acquired from a corpus environment, where the corpus environment includes a microblog, a forum, and a post bar, repeating the foregoing steps, until matches between the information to be replied to and all pending replies are obtained, and selecting a best matched pending reply as a reply to the information to be replied to.



ANNEALED DROPOUT TRAINING OF NEURAL NETWORKS

Thu, 20 Oct 2016 08:00:00 EDT

Systems and methods for training a neural network to optimize network performance, including sampling an applied dropout rate for one or more nodes of the network to evaluate a current generalization performance of one or more training models. An optimized annealing schedule may be generated based on the sampling, wherein the optimized annealing schedule includes an altered dropout rate configured to improve a generalization performance of the network. A number of nodes of the network may be adjusted in accordance with a dropout rate specified in the optimized annealing schedule. The steps may then be iterated until the generalization performance of the network is maximized.



SMALL-FOOTPRINT DEEP NEURAL NETWORK

Thu, 20 Oct 2016 08:00:00 EDT

Conversion of a large-footprint DNN to a small-print DNN is performed using a variety of techniques, including split-vector quantization. The small-foot print DNN may be distributed to a variety of devices, including mobile devices. Further, the small-footprint DNN may aid a digital assistant on a device in interpreting speech input.