27th week of 2020 patent applcation highlights part 56 |
Patent application number | Title | Published |
20200210841 | MULTI-STAGE PLACEMENT OF MATERIAL IN A WELLBORE - A system for multi-stage placement of material in a wellbore includes a recurrent neural network that can be configured based on data from a multi-stage, stimulated wellbore. A computing device in communication with a sensor and a pump is operable to implement the recurrent neural network, which may include a long short-term neural network model (LSTM). Surface data from the sensor at each observation time of a plurality of observation times is used by the recurrent neural network to produce a predicted value for a response variable at a future time, and the predicted value for the response variable is used to control a pump being used to place the material. | 2020-07-02 |
20200210842 | MULTI-OBJECTIVE GENERATORS IN DEEP LEARNING - Machine-learning data generators use an additional objective to avoid generating data that is too similar to any previously known data example. This prevents plagiarism or simple copying of existing data examples, enhancing the ability of a generator to usefully generate novel data. A formulation of generative adversarial network (GAN) learning as the mixed strategy minimax solution of a zero-sum game solves the convergence and stability problem of GANs learning, without suffering mode collapse. | 2020-07-02 |
20200210843 | TRAINING AND APPLICATION METHOD OF A MULTI-LAYER NEURAL NETWORK MODEL, APPARATUS AND STORAGE MEDIUM - The present disclosure provides a training and application method of a multi-layer neural network model, apparatus and storage medium. A number of channels of a filter in at least one convolutional layer in the multi-layer neural network model is expanded, and a convolution computation is performed by using the filter after expanding the number of channels, so that the performance of the network model does not degrade while simplifying the network model. | 2020-07-02 |
20200210844 | TRAINING AND APPLICATION METHOD OF A MULTI-LAYER NEURAL NETWORK MODEL, APPARATUS AND STORAGE MEDIUM - The present disclosure provides a training and application method of a multi-layer neural network model, apparatus and a storage medium. In a forward propagation of the multi-layer neural network model, the number of input feature maps is expanded and a data computation is performed by using the expanded input feature maps. | 2020-07-02 |
20200210845 | LEARNING A NEURAL NETWORK FOR INFERENCE OF SOLID CAD FEATURES - The disclosure notably relates to computer-implemented method for learning a neural network configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes providing a dataset including freehand drawings each representing a respective 3D shape, and learning the neural network based on the dataset. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape. | 2020-07-02 |
20200210846 | METHOD AND APPARATUS FOR SEISMIC IMAGING PROCESSING WITH ENHANCED GEOLOGIC STRUCTURE PRESERVATION - A method for seismic processing includes steps of seismic signal forward propagation and seismic data back propagation. The subsurface medium image is created after correlating and summarizing forward and backward propagation results. To address migration footprint and noise due to the incomplete data acquisition aperture and migration approximation in the migration operator, the iteration inversion strategy incorporates tensor flow calculated from seismic image. A regularization operator based on structure tensor of image is applied to seismic image inversion. | 2020-07-02 |
20200210847 | ENSEMBLING OF NEURAL NETWORK MODELS - A method includes determining, by a processor of a computing device, a subset of models included in a plurality of models generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method includes aggregating the subset of models to generate an ensembler. The ensembler, when executed on an input, provides at least a portion of the input to each model of the subset of models to generate a plurality of intermediate outputs. An ensembler output of the ensembler is based on the plurality of intermediate outputs. The method further includes executing the ensembler on input data to determine the ensembler output. | 2020-07-02 |
20200210848 | DEEP LEARNING TESTING - A specification of a property required to be upheld by a computerized machine learning system is obtained. A training data set corresponding to the property and inputs and outputs of the system is built. The system is trained on the training data set. Activity of the system is monitored before, during, and after the training. Based on the monitoring, performance of the system is evaluated to determine whether the system, once trained on the training data set, upholds the property. | 2020-07-02 |
20200210849 | TRANSACTION ANOMALY DETECTION USING ARTIFICIAL INTELLIGENCE TECHNIQUES - Systems and methods for anomaly detection includes accessing first data comprising a plurality of historical reversion transactions. A plurality of legitimate transactions are determined from the plurality of historical reversion transactions. An autoencoder is trained using the plurality of legitimate transactions to generate a trained autoencoder capable of measuring a given transaction for similarity to the plurality of legitimate transactions. A first reconstructed transaction is generated by the trained autoencoder using a first transaction. The first transaction is determined to be anomalous based on a reconstruction difference between the first transaction and the first reconstructed transaction. | 2020-07-02 |
20200210850 | Imaging Modality Smart Find Maintenance Systems and Methods - Methods, apparatus, systems and articles of manufacture to provide an image modality maintenance smart find are disclosed. The example method includes identifying an imaging device based on an image of the imaging device. The method further includes determining at least one of a make, a model, or a modality of the imaging device based on the identification. The method further includes identifying a fleet of imaging devices corresponding to the imaging device. The method further includes storing error information corresponding to an issue of the imaging device in correspondence with the fleet of imaging devices and update a model corresponding to the fleet based on the error information. The method further includes deploying the model to a device of a technician. | 2020-07-02 |
20200210851 | AUGMENTING NEURAL NETWORKS - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations. One of the methods includes maintaining, by a computational graph system that manages execution of computational graphs representing neural network operations for users of the computational graph system, data specifying a plurality of pre-trained neural networks, wherein each of the pre-trained neural networks is a neural network that has been trained on training data to determine trained values of the respective parameters of the neural network; obtaining data specifying a user computational graph representing neural network operations, the user computational graph comprising a plurality of nodes connected by edges; identifying (i) an insertion point after a first node in the user computational graph and (ii) a particular pre-trained neural network from the plurality of pre-trained neural networks; and inserting a remote call node into the user computational graph. | 2020-07-02 |
20200210852 | TRANSCRIPTOME DECONVOLUTION OF METASTATIC TISSUE SAMPLES - A platform for transcriptome deconvolution of gene expression data is provided and may be used in assessing metastatic cancer samples. The deconvolution is performed using an unsupervised clustering technique, such as grade of membership, that allows for samples to be assigned to multiple clusters during a training process. A deconvolution gene expression model is generated as a result and is used for accurate assess of metastases in subsequent samples. | 2020-07-02 |
20200210853 | OPTIMIZATION CALCULATION METHOD AND INFORMATION PROCESSING APPARATUS - An optimization calculation method includes: generating, by a computer, current generation individuals with a selected previous generation individual as a parent individual; evaluating each current generation individual by using a predetermined evaluation function; calculating a current generation constraint condition value based on a previous generation constraint condition value and a constraint condition provisional value which is achieved by more than half of the current generation individuals; determining whether a result of the evaluation for each current generation individual satisfies the current generation constraint condition value; determining a predetermined offset based on an attribute of each individual, which is generated by a mutation generating process, among individuals having the evaluation results satisfying the current generation constraint condition value; and adding the predetermined offset to a random number used to generate each next generation individual by the mutation generating process. | 2020-07-02 |
20200210854 | SYSTEM AND METHOD FOR FAULT DETECTION OF COMPONENTS USING INFORMATION FUSION TECHNIQUE - An example method comprises receiving historical sensor data of a first time period, the historical data including sensor data of a renewable energy asset, extracting features, performing a unsupervised anomaly detection technique on the historical sensor data to generate first labels associated with the historical sensor data, performing at least one dimensionality reduction technique to generate second labels, combining the first labels and the second labels to generate combined labels, generating one or more models based on supervised machine learning and the combined labels, receiving current sensor data of a second time period, the current sensor data including sensor data of the renewable energy asset, extracting features, applying the one or more models to the extracted features of the current sensor data to create a prediction of a future fault in the renewable energy asset, and generating a report including the prediction of the future fault in the energy asset. | 2020-07-02 |
20200210855 | DOMAIN KNOWLEDGE INJECTION INTO SEMI-CROWDSOURCED UNSTRUCTURED DATA SUMMARIZATION FOR DIAGNOSIS AND REPAIR - An information synthesis system for generating a knowledge base injects domain knowledge into semi-crowdsourced summarization pipelines for extracting information from unstructured data sources. The summarization pipeline includes chains of tasks completed by crowd workers and/or machined. The information synthesis system distributes the tasks to crowd workers and/or machines. Task responses are processed and aggregated to determine new information that is used to update the knowledge base. | 2020-07-02 |
20200210856 | METHOD AND SYSTEM FOR EXCHANGE OF PACKETS PERTAINING TO AN INSTRUMENT - The present disclosure relates to a method and system for exchanging packets of information pertaining to an instrument. Data pertaining to the instrument is obtained from internal and external sources, which may be governmental or non-governmental. The obtained data undergoes a process of clustering and dimensional reduction to arrive at cleaned and optimised data attributes. A predictive model is built using those data attributes. A testing provision is included in the proposed method and system that allows for validation of the constructed model by using test data and comparing the predictions with actual values. Upon validation, the model predicts one or more packets of information that can have a bearing on the exchange of packets pertaining to the instrument. | 2020-07-02 |
20200210857 | DECISION INTELLIGENCE SYSTEM AND METHOD - A decision intelligence system permits a data expert to input information to define business questions and a business knowledge model. A semantic ontology is generated from the business knowledge model. The business knowledge model is mapped to data sources and used to generate information for generating APIs for generating views of business data, such as machine generated data. | 2020-07-02 |
20200210858 | NETWORK EMBEDDING METHOD - A computer-implemented conditional network embedding method to map nodes of a given network, comprises a set of links between the nodes, onto points in a d-dimensional Euclidean space wherein d is equal to 1 or larger. The method comprises identifying and modeling information about structural properties of the network related to the nodes and the set of links between them, and searching an embedding which maps information of the network which is not part of or implied by these structural properties onto points in the d-dimensional Euclidean space. | 2020-07-02 |
20200210859 | PREDICTING FATIGUE OF AN ASSET THAT HEALS - The example embodiments are directed to a system and method which can predict a degradation in the health of an asset that heals based on data sensed from a machine or equipment operated by the asset that heals and in consideration of healing of the asset. In one example, a method may include one or more of storing time-series data of an operation of a machine, predicting a fatigue value of an operator of the machine via a predictive model that comprises a Rainflow counting algorithm that determines a degradation of the operator based on a changing attribute in the time-series data and a healing function that determines a healing component of the operator based on rest of the operator, and outputting information about the predicted fatigue value via a user interface. | 2020-07-02 |
20200210860 | PERSONAL DATA HUB - The present invention provides an apparatus, method, and system for an entity to receive an inference or profile of characteristics that has been generated from personal or non-personal data related to an individual, where the inference or profile of characteristics has been provisioned to the entity by command of the individual. The provisioning of an inference or profile of characteristics related to the individual by the direct action of the individual, serves as explicit permission for the entity to employ the individual's inference or profile of characteristics for the advancement of the entity's business interests. With most, if not all, data privacy regimes requiring the prior explicit consent of an individual for an entity to use the individual's personal or non-personal data, either for internal or external purposes, the present invention can significantly ease the burden on an entity associated with meeting the compliance requirements mandated by regulations in the governmental jurisdictions in which they may, or do, operate. | 2020-07-02 |
20200210861 | AUTOMATED QUALITY ASSESSMENT OF PHYSIOLOGICAL SIGNALS - Methods and systems may provide for receiving a physiological signal from a sensor configuration associated with a mobile device. A qualitative analysis may be conducted for each of a plurality of noise sources in the physiological signal to obtain a corresponding plurality of qualitative ratings. In addition, at least the plurality of qualitative ratings may be used to determine whether to report the physiological signal to a remote location. In one example, a quantitative analysis is conducted for each of the plurality of noise sources to obtain an overall quality level, wherein the overall quality level is also used to determine whether to report the physiological signal to the remote location. | 2020-07-02 |
20200210862 | SYSTEMS AND METHODS FOR EXTENDING REASONING CAPABILITY FOR DATA ANALYTICS IN INTERNET-OF-THINGS (IoT) PLATFORM - Systems and methods for extending reasoning capability for data analytics in Internet of Things (IoT) platform(s) are provided. Traditional systems and methods for executing IoT analytics tasks suffer as IoT analytics techniques are generated in different programming language platforms, and this leads to a manual intervention or an asynchronous and sequential analysis of IoT analytics task(s). Embodiments of the method disclosed provide for overcoming the limitations faced by the traditional systems and methods by dynamically creating procedural functions from a plurality of programming languages upon determining an absence of pre-defined procedural functions, and extracting, using the dynamically created procedural functions, one or more semantic rules in a real-time, wherein the one or more semantic rules extend a reasoning capability for executing the one or more data analytics tasks in a plurality of IoT platforms. | 2020-07-02 |
20200210863 | BEHAVIOR ANALYSIS SYSTEM, BEHAVIOR ANALYSIS METHOD, AND STORAGE MEDIUM - Provided is a behavior analysis system including: a generation unit that generates a behavior data group including a plurality of behavior data on an analysis target basis; a conversion unit that converts the behavior data group of each of a plurality of analysis targets by converting a parameter which depends on the analysis target out of parameters included in the behavior data group into a parameter which does not depend on the analysis target; and an analysis unit that performs analysis by using the converted behavior data group of the plurality of analysis targets. | 2020-07-02 |
20200210864 | METHOD FOR DETECTING COMMUNITY STRUCTURE OF COMPLICATED NETWORK - The present invention discloses a method for detecting the community structure in complicated networks. In order to improve the global convergence performance of the differential evolution algorithm, three main evolution operations are redesigned, including a classification-based adaptive mutation strategy, a dynamic adaptive parameter adjustment strategy, and a historical information-based selection operation. On the other hand, in order to make better use of the network topology information, the present invention provides a neighborhood information-based improved community adjustment strategy to ensure that sufficient search space is provided for the global optimal community division, while reducing the search space of DE. Finally, the present invention provides a new modularity optimization algorithm CDEMO based on differential evolution algorithm. | 2020-07-02 |
20200210865 | LOG ANALYSIS SYSTEM, LOG ANALYSIS METHOD, LOG ANALYSIS PROGRAM, AND STORAGE MEDIUM - Provided is a log analysis system including: an identifying unit that identifies transactions from logs output from a device; a grouping unit that categorizes the transactions having both the same log related to start and the same log related to end into the same group; a learning unit that creates a learning model that defines the number of occurrences on a log type basis in the transactions of the same group; and an inspection unit that inspects a transaction of an inspection target based on the learning model. | 2020-07-02 |
20200210866 | INFORMATION PROCESSING DEVICE, INFERENCE PROCESSING DEVICE, AND INFORMATION PROCESSING SYSTEM - An information processing device includes: a main processor. The main processor receives resource information related to a processing status from each of N processors assuming that N is an integral number equal to or larger than 2, applies the received resource information of the N processors to a computational expression, and calculates processing times corresponding to a processing request from an application for the respective N processors, selects one processor from among the N processors based on the processing times of the N processors, and transmits the processing request to the one processor. | 2020-07-02 |
20200210867 | MULTI-CLIENT SERVICE SYSTEM PLATFORM - A modular machine learning-as-a-service (MLAAS) system uses machine learning to respond to tasks without requiring machine learning modeling or design knowledge by its users. The MLAAS system receives an inference request including a model identifier and a target defining features for use in processing the inference request. The features correspond to a task for evaluation using a machine learning model associated with the model identifier. An inference outcome is generated by processing the inference request using the target as input to the model. Feedback indicating an accuracy of the inference outcome with respect to the task is later received and used to generate a training data set, which the MLAAS can use to further train model used to generate the inference outcome. As a result, the training of a machine learning model by the MLAAS system is limited to using data resulting from an inference performed using that model. | 2020-07-02 |
20200210868 | SYSTEMS AND METHODS FOR MACHINE LEARNING IN PATIENT PLACEMENT - The present disclosure relates to systems and methods for determining one or more appropriate treatment facilities for patient placement. A machine learning system may perform operations. The operations may receive a patient data set including patient attributes and patient location metrics; access a plurality of data sets for a plurality of medical facilities, the plurality of data sets include facility capacity, location, and capability metrics for each of the plurality of medical facilities; apply a model to match the patient data set with at least one of the plurality of medical facility data sets based on at least one of the patient attributes and patient location metrics and at least one of the facility capacity, location, and capability metrics; determine, based on the application of the model, one or more likelihoods of acceptance associated with each match. | 2020-07-02 |
20200210869 | GATEWAY AND METHOD FOR TRANSFORMING A DESCRIPTION OF AN INDUSTRIAL PROCESS EQUIPMENT INTO A DATA INFORMATION MODEL - Modern industrial processes demand flexibility in terms of how data flows are structured in an automation pyramid. Instead of only upward and downward flows, the data should be accessible directly at each level of the pyramid. A gateway for facilitating an integration of process equipment within an industrial environment supporting an open industry standard is provided. Field devices having characteristics, capabilities and/or requirements that are expressed by a description language for industrial process equipment such as EDDL are integrated into a contemporary communication environment enabling a direct data access. The communication environment is operated based on a semantically enriched and graph-based data information model such as provided by OPC UA. | 2020-07-02 |
20200210870 | Forecasting Demand Using Hierarchical Temporal Memory - In general, embodiments of the present invention provide systems, methods and computer readable media to forecast demand by implementing an online demand prediction framework that includes a hierarchical temporal memory network (HTM) configured to learn temporal patterns representing sequences of states of time-series data collected from a set of one or more data sources representing demand and input to the HTM. In some embodiments, the HTM learns the temporal patterns using a Cortical Learning Algorithm. | 2020-07-02 |
20200210871 | ADAPTIVE DEVICE TYPE CLASSIFICATION - Systems and methods for device type classification system include a rules engine and a machine learning engine. The machine learning engine can be trained using device type data from multiple networks. The machine learning engine and the rules engine can receive data for devices on a network at a first point in time. The data can be submitted to a rules engine and the machine learning engine, which each produce device type probabilities for devices on the network. The device type probabilities from the rules engine and the machine learning engine can be processed to determine device types for one or more devices on the network. As more data becomes available at later points in time, the additional data can be provided to the rules engine and the machine learning engine to update the device type determinations for the network. | 2020-07-02 |
20200210872 | SYSTEM AND METHOD FOR DETERMINING COSMETIC OUTCOME EVALUATION - A method, system and computer readable medium provides for a multi-dimensional data integration for estimating cosmetic outcomes in a computing environment including collecting sample data associated with cosmetic outcomes; receiving input defining one or more schemas for organizing the collected sample data; profiling the sample data to determine one or more metrics associated with the sample data, the metrics including at least a physical beauty metric, a genuineness metric and a self-esteem metric; generating one or more rules based on the one or more schemas, the rules including at least an attractiveness rule; and generating a functional estimation system based on the generated one or more rules, for use in processing a data input, the generated functional type system providing an estimation of cosmetic outcome. | 2020-07-02 |
20200210873 | TIME-SERIES FAULT DETECTION, FAULT CLASSIFICATION, AND TRANSITION ANALYSIS USING A K-NEAREST-NEIGHBOR AND LOGISTIC REGRESSION APPROACH - A method includes receiving historical time-series data and generating training data comprising a plurality of randomized data points associated with the historical time-series data. The historical time-series data was generated by one or more sensors during one or more processes. The method further includes training a logistic regression classifier based on the training data to generate a trained logistic regression classifier. The trained logistic regression classifier is associated with a logistic regression that indicates a location of a transition pattern from a first data point to a second data point. The transition pattern reflects about a reflection point located on the transition pattern. The trained logistic regression classifier is capable of indicating a probability that new time-series data generated during a new execution of the one or more processes matches the historical time-series data. | 2020-07-02 |
20200210874 | METHOD AND SYSTEM FOR THE CREATION OF FUZZY COGNITIVE MAPS FROM EXTRACTED CONCEPTS - The present invention is a computer-implemented method for generating a cognitive map, comprising: identifying, by one or more processors, a subject matter node, wherein it is determined if the subject matter is pre-exiting in a cognitive map; incorporating, by one or more processors, the subject matter node into the cognitive map; establishing, by one or more processors, a relationship between the subject matter node and the pre-existing nodes, where the relationship is determined based on the subject matter node relative to the pre-existing nodes; categorizing, by one or more processors, the subject matter node as an exogenous or a non-exogenous node; and generating, by one or more processors, a graphical representation of the cognitive map. | 2020-07-02 |
20200210875 | METHOD AND SYSTEM FOR PREDICTIVE ANALYTICS THROUGH THE USE OF FUZZY COGNITIVE MAPS IN A COMPUTING WITH WORDS ARCHITECTURE - The present invention is a computer-implemented method for calculating the relationship between concepts, comprising: generating, a map of a plurality of nodes; assigning, activation values for a set of exogenous nodes; establishing, a set of causal relationships between nodes; iterating, the map until a convergence state is reached by the set of non-exogenous nodes, wherein the convergence state represents a temporary equilibrium condition between the connected nodes; assigning linguistic terms to the node states and causal relationships based on a mapping between word index values and linguistic terms; and calculating the states of the set of non-exogenous nodes based on the linguistic terms associated with all of the connected nodes. | 2020-07-02 |
20200210876 | SYSTEMS AND METHODS FOR MACHINE LEARNING USING ADIABATIC QUANTUM COMPUTERS - A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the digital processor can operate as a restricted Boltzmann machine. The computational system can operate as a quantum-based deep belief network operating on a training data-set. | 2020-07-02 |
20200210877 | REMOVAL OF WIREBONDS IN QUANTUM HARDWARE - A method includes depositing a first layer on a portion of a first surface of a quantum hardware, the portion of the first surface comprising a set of wirebonds. The method further includes coupling the set of wirebonds to the first layer. The method further includes removing the first layer and the set of wirebonds from the first surface of the quantum hardware. In an embodiment, the first layer is an inert polymer in solution. | 2020-07-02 |
20200210878 | REMOVAL OF WIREBONDS IN QUANTUM HARDWARE - A product causes a method to be performed, the method includes depositing a first layer on a portion of a first surface of a quantum hardware, the portion of the first surface comprising a set of wirebonds. The method further includes coupling the set of wirebonds to the first layer. The method further includes removing the first layer and the set of wirebonds from the first surface of the quantum hardware. In an embodiment, the first layer is an inert polymer in solution. | 2020-07-02 |
20200210879 | MULTI-MODE QUBIT READOUT AND QUBIT STATE ASSIGNMENT - Systems, computer-implemented methods, and computer program products to facilitate external port measurement of qubit port responses are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an analysis component that can analyze responses of a multi-mode readout device coupled to a qubit. The computer executable components can further comprise an assignment component that can assign a readout state of the qubit based on the responses. In some embodiments, the multi-mode readout device can be electrically coupled to at least one of the qubit or an environment of the qubit based on a defined electrical coupling value. | 2020-07-02 |
20200210880 | RECONFIGURATION OF EMBEDDED SERVICES ON DEVICES USING DEVICE FUNCTIONALITY INFORMATION - A system and method for reconfiguration of embedded services on devices using device functionality information, is provided. The system includes an AI-enabled device and a server. The server receives first usage information associated with the AI-enabled device and second usage information associated with a plurality of embedded AI services on the AI-enabled device. Further, the server generates an AI model based on the received first usage information and the received second usage information and discovers, from the plurality of embedded AI services, a first embedded AI service that requires a model response. The server outputs the model response using the generated AI model and reconfigures the discovered first embedded AI service based on the model response. The model response includes first functionality information and second functionality information associated with the AI-enabled device. | 2020-07-02 |
20200210881 | CROSS-DOMAIN FEATURING ENGINEERING - The example embodiments are directed to a continuously expanding cross-domain featuring engineering system. In one example, a method may include one or more of storing predictive features in a cross-domain data store, the predictive features previously used in machine learning modeling in a plurality of different domains, receiving data of an asset included in a target domain and information about an evaluation attribute associated with the asset in the target domain, determining a predictive feature in the received data based on a previously used predictive feature stored in the cross-domain data store which is associated with a machine learning model in a different domain and the evaluation attribute, and outputting the determined predictive feature for display via a user interface. | 2020-07-02 |
20200210882 | MACHINE LEARNING BASED FUNCTION TESTING - A method for determining the performance metric of a function may include interpolating the performance metric of the function relative to a known performance metric of a reference function. The performance metric of the function may be interpolated based on a first difference in a performance of the function measured by applying a first machine learning model and a performance of the function measured by applying a second machine learning model. The performance metric of the function may be further interpolated based on a second difference in a performance of the reference function measured by applying the first machine learning model and a performance of the reference function measured by applying the second machine learning model. The function may be deployed to a production system if the performance metric of the function exceeds a threshold value. Related systems and articles of manufacture, including computer program products, are also provided. | 2020-07-02 |
20200210883 | ACCELERATION OF MACHINE LEARNING FUNCTIONS - A multi-staged sample and seed machine-learning training technique is presented. A sample proportion of a training data set is fed to a machine-learning algorithm (MLA) for purposes of configuring functions of the MLA to predict an output with a desired degree of accuracy. When iterating the sample proportion, if a deviation in an incrementally produced current accuracy of the MLA does not exceed a threshold, the sampled proportion is increased. This continues until the current degree of accuracy meets or exceeds the desired degree of accuracy, which is an indication that the functions of the MLA are configured as a desired model for producing the predicted output when the MLA is presented with input that may or may not have been associated with the training data set. | 2020-07-02 |
20200210884 | REMOVING UNNECESSARY HISTORY FROM REINFORCEMENT LEARNING STATE - Methods and systems for a reinforcement learning system. A spatial and temporal representation of an observed state of an environment is encoded. A previous state is estimated from a given state and a size of a reward is adjusted based on a difference between the estimated previous state and the previous state. | 2020-07-02 |
20200210885 | DETERMINING AVAILABILITY OF NETWORK SERVICE - Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining availability of network service. In some implementations, a request indicating a location and a communication service level is received. A first subset of service providers or communication technologies is determined based on outputs generated by multiple first machine learning models each trained to predict service availability for different service providers or communication technologies. A second subset is selected from the first subset based on outputs generated by multiple second machine learning models trained to predict availability of different communication service levels for different service providers or communication technologies. At least one service provider or communication technology is selected from the second subset based on output generated by a third machine learning model. A response to the request indicating the selected service provider or communication technology is provided. | 2020-07-02 |
20200210886 | Prediction for Time Series Data Using a Space Partitioning Data Structure - Techniques are disclosed for a computer system to predict a next sample for a data stream that specifies data values of one or more variables. A current subset of data values and previous subsets of data values is determined, and polyline simplification techniques may then be used on the subset to produce a reduced-sample current subset of data values that are converted to an angular coordinate system. A space partitioning data structure such as a k-dimensional tree that stores converted reduced-sample previous subsets of the data stream may then be traversed to determine one or more nearest neighbors to the current subset. The predicted next sample for the data stream may be generated from the nearest neighbors. The space partitioning data structure may be updated to include the current subset, and the process may be repeated with a new current subset. | 2020-07-02 |
20200210887 | APPROACHES FOR DETERMINING SENSOR CALIBRATION - Systems, methods, and non-transitory computer-readable media can determine first sensor data captured by a first sensor of a vehicle. Second sensor data captured by a second sensor of the vehicle can be determined. Information describing the first sensor data and the second sensor data can be provided to a machine learning model trained to predict whether a pair of sensors are calibrated or mis-calibrated based on sensor data captured by the pair of sensors. A determination is made whether the first sensor and the second sensor are calibrated or mis-calibrated based on an output from the machine learning model. | 2020-07-02 |
20200210888 | METHOD AND SYSTEM FOR SIMILARITY-BASED MULTI-LABEL LEARNING - A system is provided for facilitating multi-label classification. During operation, the system maintains a set of training vectors. A respective vector represents an object and is associated with one or more labels that belong to a label set. After receiving an input vector, the system determines a similarity value between the input vector and one or more training vectors. The system further determines one or more labels associated with the input vector based on the similarity values between the input vector and the training vectors and their corresponding associated labels. | 2020-07-02 |
20200210889 | INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, PROGRAM, AND VEHICLE - An information processing system receives first travel histories from vehicles that belong to vehicle type A, learns based on the first travel histories to build a first driver model that represents relation between travel situations and behaviors of the vehicles that belong to a first vehicle type, receives second travel histories from vehicles that belong to vehicle type X that is different from vehicle type A, and performs transfer learning in which the second travel histories are used for the first driver model to build a second driver model that represents relation between travel situations and behaviors of the vehicles that belong to vehicle type X. | 2020-07-02 |
20200210890 | TRAJECTORY CLUSTER MODEL FOR LEARNING TRAJECTORY PATTERNS IN VIDEO DATA - Techniques are disclosed for analyzing and learning behavior in an acquired stream of video frames. In one embodiment, a trajectory analyzer clusters trajectories of objects depicted in video frames and builds a trajectory model including the trajectory clusters, a prior probability of assigning a trajectory to each cluster, and an intra-cluster probability distribution indicating the probability that a trajectory mapping to each cluster is least various distances away from the cluster. Given a new trajectory, a score indicating how unusual the trajectory is may be computed based on the product of the probability of the trajectory mapping to a particular cluster and the intra-cluster probability of the trajectory being a computed distance from the cluster. The distance used to match the trajectory to the cluster and determine intra-cluster probability is computed using a parallel Needleman-Wunsch algorithm, with cells in antidiagonals of a matrix and connected sub-matrices being computed in parallel. | 2020-07-02 |
20200210891 | METHOD OF AND SYSTEM FOR GENERATING TRAINING SET FOR MACHINE LEARNING ALGORITHM (MLA) - There is disclosed a computer-implemented method and system for generating a set of training objects for training a machine learning algorithm (MLA) to determine query similarity based on textual content thereof, the MLA executable by the system. The method comprises retrieving, from a search log database of the system, a first query and other queries with associated search results. The method then comprises selecting a subset of query pairs such that: a query difference in queries in the pair is minimized and a results difference in respective search results is maximized | 2020-07-02 |
20200210892 | ECONOMIC OPTIMIZATION FOR PRODUCT SEARCH RELEVANCY - In one embodiment, a method is illustrated as including defining a set of perspective objects capable of being placed onto a modified web page, monitoring parameters of a web page, the parameters including a number of times a current object is executed on the web page, using an Artificial Intelligence (AI) algorithm to determine a perspective object with a preferred Return On Investment (ROI), and selecting the perspective object to be placed onto the modified web page. | 2020-07-02 |
20200210893 | Learning Method, Learning Program, Learning Device, and Learning System - Provided is a learning method, a learning program, a learning device, and a learning system, for training a classification model, to further raise the correct answer rate of classification by the classification model. The learning method includes execution of generating one piece of composite data by compositing a plurality of pieces of training data of which classification has each been set, or a plurality of pieces of converted data obtained by converting the plurality of pieces of training data, at a predetermined ratio, inputting one or a plurality of pieces of the composite data into the classification model, and updating a parameter of the classification model so that classification of the plurality of pieces of training data included in the composite data is replicated at the predetermined ratio by output of the classification model, by a computer provided with at least one hardware processor and at least one memory. | 2020-07-02 |
20200210894 | ANALYSIS APPARATUS, ANALYSIS METHOD, AND ANALYSIS PROGRAM - An analysis apparatus comprises: a processor; and a storage device that stores a prediction model that predicts results for contributing factors of a group of events, wherein the processor executes: a prediction error calculation process in which, on the basis of a first prediction value attained by providing the prediction model with a first appearance frequency for contributing factors of a first event among the group of events, and results corresponding to the first appearance frequency, a prediction error of the first prediction value is calculated; and an error factor extraction process in which, on the basis of a correlation between a second appearance frequency for a contributing factor of a second event among the group of events and the prediction error calculated by the prediction error calculation process, an error factor of the prediction error is extracted from among the contributing factors of the first event. | 2020-07-02 |
20200210895 | TIME SERIES DATA PROCESSING DEVICE AND OPERATING METHOD THEREOF - The time series data processing device according to an embodiment of the inventive concept includes a preprocessor, a learner, and a predictor. The preprocessor preprocesses time series data to generate interval data, interpolation data, and masking data. The learner generates a weight value group of a prediction model that generates a feature weight value and a time series weight value, based on the interval data, the interpolation data, and the masking data. The feature weight value depends on a time and a feature of the time series data and the time series weight value depends on a time flow of the time series data. The predictor generates a feature weight value and a time series weight value, based on the weight value group, and generates a prediction result, based on the feature weight value and time series weight value. | 2020-07-02 |
20200210896 | METHOD AND SYSTEM FOR REMOTE TRAINING OF MACHINE LEARNING ALGORITHMS USING SELECTED DATA FROM A SECURED DATA LAKE - A system and a method for remote training of a machine learning algorithm using selected data from a secured data lake are provided herein. The method may include the following steps: inputting client parameters onto a secured server having said secured data lake; collating raw data stored within said secured data lake, according to said client parameters, to yield selected data, wherein said selected data and said raw data are inaccessible to said client; uploading said machine learning algorithm from said client to said secured server; and training said machine learning algorithm on said secured server, using said selected data, to yield a trained machine learning algorithm. | 2020-07-02 |
20200210897 | System, Method, and Computer Program Product for Data Placement - A system, method, and computer program product for data placement may include obtaining feature data associated with a set of feature inputs of a machine learning model, determining a probability that a subset of the feature data is concurrently used as the set of feature inputs for the machine learning model, and storing the subset of the feature data on a same cache node or server of a plurality of cache nodes or servers based on the probability. | 2020-07-02 |
20200210898 | INFORMATION PROCESSING APPARATUS AND METHOD OF CONTROLLING THE SAME - An information processing apparatus comprises: an obtaining unit configured to obtain an estimation result estimated using an estimation model; a determination unit configured to determine a conversion table configured to correct the estimation result using the estimation model based on an estimation accuracy in the estimation model; and a correction unit configured to correct the estimation result based on the conversion table. | 2020-07-02 |
20200210899 | MACHINE LEARNING MODEL TRAINING METHOD AND DEVICE, AND ELECTRONIC DEVICE - A machine learning model training method includes: classifying samples having risk labels in a training sample set as positive samples and classifying samples without risk labels in the training sample set as negative samples; training a risk model with a machine learning method based on the positive samples and the negative samples; obtaining a risk score for each of the negative samples based on the trained risk model; identifying one or more negative samples in the training sample set that have a risk score greater than a preset threshold value; re-classifying the one or more negative samples in the training sample set that have a risk score greater than the preset threshold value as re-classified positive samples to generate an updated training sample set from the training sample set; and re-training the risk model with the machine learning method based on the updated training sample set. | 2020-07-02 |
20200210900 | SYSTEM AND METHOD FOR AN OPTIMIZED, SELF-LEARNING AND SELF-ORGANIZING CONTACT CENTER - A system and method for an optimized, self-learning and self-organizing contact center has been developed. This system and method uses principles and tools of information theory, including the latent Dirichlet allocation which reduces information to specific predetermined topics and a distribution of topic related words to infer its hidden, generative underpinnings so to self-organize a contact center, infer its desired electronic versus human make up, and optimally route all customer requests to an electronic resource or a specific human agent best suited to respond to the request for maximal business value per interaction. | 2020-07-02 |
20200210901 | DYNAMIC LEARNING METHOD AND SYSTEM FOR ROBOT, ROBOT AND CLOUD SERVER - A dynamic learning method for a robot includes a training and learning mode. The training and learning mode includes the following steps: dynamically annotating a belonging and use relationship between an object and a person in a three-dimensional environment to generate an annotation library; acquiring a rule library, and establishing a new rule and a new annotation by means of an interactive demonstration behavior based on the rule library and the annotation library; and updating the new rule to the rule library and updating the new annotation to the annotation library when it is determined that the established new rule is not in conflict with rules in the rule library and the new annotation is not in conflict with annotations in the annotation library. | 2020-07-02 |
20200210902 | RESERVATION SYSTEM - The reservation system hereof operates to provide a collaborative network whereby users provides user information including preferences to a administrative module that operates to create a user's preference profile for each user having a reservation for an accommodation at a location for a specific period of time and places each user in a group based on the user's preference profile and cooperates with the room administrative system at the location to assign accommodations at the location and for the specific period of time based on the group. | 2020-07-02 |
20200210903 | MULTI-PARTY EVENT RESERVATION SYSTEM AND METHOD - Systems, devices, and methods for a novel computing device and method for enabling users to receive data regarding specific events based on the date, location, and artist performing at the event. A user can then select the desired event based on the criteria provided by the computing device. The user can determine which event reservation he or she wishes to join from a selection of event reservations already established by other users. | 2020-07-02 |
20200210904 | AUTOMATED, CONDITIONAL EVENT TICKETING, RESERVATION, AND PROMOTION TECHNIQUES IMPLEMENTED OVER COMPUTER NETWORKS - Various techniques are described herein for providing ticketing reservation and purchasing functionality for enabling and/or facilitating users in performing activities/operations relating to group ticket reservations and/or automated conditional ticket purchases for various types of events which are scheduled to occur at one or more different venues. | 2020-07-02 |
20200210905 | Systems and Methods for Managing Networked Vehicle Resources - A method and apparatus for managing a networked vehicle resource sharing facility, the method and system provide defining a geographical area as a work region; storing, in a data structure, data relating to vehicle hire bookings beginning inside the work region, wherein the booking information for each booking includes a default delay time; applying a rule to determine that an additional delay condition or fully booked condition is satisfied within the work region; and in response to positively determining, automatically introducing an additional delay or a fully booked setting, respectively, to at least some of the vehicle hire bookings inside the work region. | 2020-07-02 |
20200210906 | EVENT-BASED SERVICE ENGINE AND SYSTEM - Methods are disclosed for providing a connected context based experience to a user during a traveling event. A processing system including a processor detects a start of a traveling event for a user, establishes a context data sharing community for the traveling event, wherein the context data sharing community comprises at least one context data source device and a plurality of service agents, where each service agent is expected to provide a service to the user for a duration specified for the traveling event, determines at least one recommendation or at least one action from context data associated with the user received from the at least one context data source device, wherein the context data comprises a purpose of the user for the traveling event, and provides the at least one recommendation to at least one service agent of the plurality of service agents for presentation to the user. | 2020-07-02 |
20200210907 | UTILIZING ECONOMETRIC AND MACHINE LEARNING MODELS TO IDENTIFY ANALYTICS DATA FOR AN ENTITY - A device receives and processes current, forecasted, and historical entity information, associated with an entity, to generate processed information. The device calculates an operating enterprise value for the entity based on the processed information and bifurcates the operating enterprise value into a current value associated with current operations of the entity and a future value associated with investments of the entity. The device determines a growth rate based on the current value and the future value, and processes the current value, the future value, and the growth rate, with a first model, to determine underlying drivers of total returns for stakeholders associated with the entity. The device processes the underlying drivers of total returns for stakeholders and revenue, costs, assets, and liabilities associated with the entity, with a second model, to identify analytics data for the entity, and performs actions based on the analytics data identified for the entity. | 2020-07-02 |
20200210908 | DYNAMIC OPTIMIZATION FOR JOBS - The disclosed embodiments provide a system for performing dynamic job bidding optimization. During operation, the system obtains historical data containing a time series of interactions with a job. Next, the system uses the historical data to calculate an initial price of a job based on a predicted number of interactions with the job. The system then determines a first dynamic adjustment to the initial price that improves utilization of a budget for the job and a second dynamic adjustment to the initial price that improves a performance of the job. Finally, the system applies the first and second adjustments to the initial price to produce an updated price for the job and delivers the job within an online system based on the updated price. | 2020-07-02 |
20200210909 | Autonomous Shuffling Of Pallets Of Items In A Warehouse - Examples described may enable rearrangement of pallets of items in a warehouse to an optimal layout. An example method includes receiving real-time item information including pallet locations in a warehouse and real-time inventory of items arranged on the pallets; determining a likelihood of demand for future access to the pallets based on a pallet relocation history and item receiving/shipment expectations; based on the real-time item information and the likelihood of demand, determining an optimal controlled-access dense grid layout in which distances of the pallets from a center of the layout are related to the likelihood of demand; receiving real-time robotics information and using the real-time robotics information to determine an amount of time to rearrange the pallets to the optimal layout; and, based on the amount of time to rearrange the pallets being less than a threshold, causing the robotic devices to rearrange the pallets to the optimal layout. | 2020-07-02 |
20200210910 | MACHINE LEARNING ARTIFICIAL INTELLIGENCE SYSTEM FOR PREDICTING HOURS OF OPERATION - An artificial intelligence system for communicating predicted hours of operation to a client device. The system may include a processor in communication with a client device and a database; and a storage medium storing instructions. When executed, the instructions in the storage medium configure the processor to: receive, from the client device, a request for hours of operation of a merchant, the request specifying a day of the week; obtain, from the database in response to the request, a set of credit card authorizations associated with the merchant; determine a selected day authorizations subset by selecting, from the set of credit card authorizations, credit card authorizations issued on the specified day of the week; generate a posted transaction array based on the selected day authorizations subset, the posted transaction array may include a plurality of time intervals and numbers of transactions for the time intervals; generate a predictions list based on the posted transaction array, the predictions list including the time intervals and prediction indications for the time intervals; and communicate the predictions list to the client device. | 2020-07-02 |
20200210911 | Workflow Management System and Method for Creating and Modifying Workflows - A workflow management system for generating workflows. The system includes a knowledgebase encoded with terms for steps, dependencies of the steps, and constraints for the steps. The system further includes a computing system programmed to receive the dependencies of the steps from the knowledgebase and to generate a workflow or a portion thereof based on the dependencies of the steps without reference to any other existing workflows. | 2020-07-02 |
20200210912 | INTEGRATED SOLUTION FOR SAFE OPERATING WORK SPACE - An integrated solution for safe operating work spaces includes systems and a computer-implemented method including the following. Information related to safety and operation of a harsh environment operation is received at a safe operating work space integration system (SOWSIS) from a plurality of non-integrated systems. The received information is analyzed by the SOWSIS, including integrating the information received from the plurality of non-integrated systems and performing a risk-based and root cause analysis using the integrated information. Actions to be performed are determined by the SOWSIS based on the analyzing and the integrated information. The actions are related to safety of the harsh environment operation. The actions are implemented by the SOWSIS. | 2020-07-02 |
20200210913 | DATABASE SYSTEM ARCHITECTURE FOR REFUND DATA HARMONIZATION - A refund tracking (RT) computing device including a processor and a memory in communication with the processor is provided. The RT computing device is configured to receive historical transaction data from a payment network or a merchant data source, the historical transaction data received in different formats, parse data fields from the historical transaction data, store the parsed data fields for each of the transactions in a respective harmonized refund data structure in a database, receive current transaction data for a current transaction from a merchant computing device, retrieve at least one harmonized refund data structure from the database, determine a refund risk score based on comparing the current transaction data to the at least one harmonized refund data structure, and transmit the refund risk score to the merchant terminal. | 2020-07-02 |
20200210914 | RISK MANAGEMENT SYSTEM INTERFACE - A method may include generating a user interface (UI) to facilitate interaction with a risk management system. The UI may include a first element indicating a rule used by the risk management system to manage risk for a client, a second element indicating effectiveness of the rule, and a third element invocable to modify the rule. The method may also include monitoring activity of the client to determine whether the activity of the client shifts the client into a different category of client; determining that the client is shifted into the different category; based on the shift, modifying the second element to include a recommended modification to the rule; and in response to receiving an interaction with the second element, applying the recommended modification to the rule. | 2020-07-02 |
20200210915 | Method and System for Monitoring Core Body Movements - A system for monitoring core body movement comprises a sensor device for collecting a data set representing a plurality of core body movements over time from a monitoring device; a processor for determining a plurality of risk scores from the data set; and an output device for indicating the risk scores. | 2020-07-02 |
20200210916 | PRIVACY MANAGEMENT SYSTEMS AND METHODS - Data processing systems and methods, according to various embodiments, are adapted for mapping various questions regarding a data breach from a master questionnaire to a plurality of territory-specific data breach disclosure questionnaires. The answers to the questions in the master questionnaire are used to populate the territory-specific data breach disclosure questionnaires and determine whether disclosure is required in territory. The system can automatically notify the appropriate regulatory bodies for each territory where it is determined that data breach disclosure is required. | 2020-07-02 |
20200210917 | APPARATUS, METHOD, PROGRAM, SIGNAL FOR DETERMINING INTERVENTION EFFECTIVENESS INDEX - A method for determining an intervention effect index for a person executing a task is provided and comprises: obtaining sensing information by at least one sensor coupled to the person, the sensing information includes first sensing information relating to performance in executing the task and second sensing information relating to an emotional state; determining, on the basis of said first sensing information, a performance value difference indicating a variation between performance in executing the task before and after an intervention is applied, the intervention representing an excitation affecting the person; estimating, on the basis of said second sensing information, an emotional value difference indicative of a variation between emotional states before and after the intervention is applied; determining the intervention effect index on the basis of said performance value difference and said emotional value difference, the intervention effect index representing an indication on effectiveness of the intervention on the person. | 2020-07-02 |
20200210918 | METHODS AND SYSTEMS FOR SCHEDULING LOCATION-BASED TASKS AND LOCATION-AGNOSTIC TASKS - Methods and systems for scheduling tasks for field professionals include: receiving a set of first requests for on-site assistance from a first set of users; receiving a set of second requests for remote assistance from a second set of users; assigning a plurality of location-based tasks associated with the set of first requests to one or more field professional; receiving real-time information associated with the one or more field professional including current location; determining based on the real-time information whether the one or more field professional can complete a location-agnostic task associated with a second request after completing a first location-based task and before starting a second location-based task; and assigning the location-agnostic task to the one or more field professional. | 2020-07-02 |
20200210919 | SYSTEMS AND METHODS FOR ASSIGNING TASKS BASED ON REAL-TIME CONDITIONS - Systems and methods for scheduling tasks to field professionals are provided. In one implementation, a system may receive a first request for an on-site service and schedule a task associated with the first request to be performed on a first scheduled date. After scheduling the task associated with the first request, the system may receive a second request from a connected device for an on-site service. The system may determine a time period that corresponds with an urgency level of the on-site service for the connected device, and schedule a task associated with the second request on a second scheduled date based on the urgency level. The first scheduled date and the second scheduled date may be the same date or different dates. Thereafter, the system may receive confirmation that the task associated with the first request and the task associated with the second request have been completed. | 2020-07-02 |
20200210920 | Machine Learning System for Demand Forecasting With Improved Date Alignment - Disclosed is a machine learning system with date alignment features for improved demand forecasting for products and/or services. The system includes an appliance for more accurately aligning days and weeks between years, including adapting to holidays and special days, in order to ascertain the date in a previous year that most closely aligns with the date in the future for which the forecast is sought. The corresponding day in one or more previous years can then be computed and demand data associated therewith can be retrieved from data storage to be used in forecasting demand on the forecast date. The most closely aligned day from a previous year can be selected such that the aligned day is positioned appropriately within the calendar week and year and the aligned day falls within a week that is positioned appropriately within the calendar month (i.e., first week, last week or middle-month weeks). | 2020-07-02 |
20200210921 | SYSTEMS AND METHODS FOR USING PREDICTED DEMAND TO OPTIMIZE TASK SCHEDULING - Methods, apparatuses, and systems for scheduling tasks to field professionals include a memory configured to store historical data associated with past demand for field professionals, a network interface, and at least one processor connectable to the network interface. The at least one processor is configured to access the memory and to: receive a set of requests reflecting a current demand for on-site services; predict imminent demand for on-site services based on the historical data; generate a schedule for a set of field professionals based on the current demand for on-site services; and reserve in the schedule availability based on the predicted imminent demand for on-site services. | 2020-07-02 |
20200210922 | PREDICTING A SUPPLY CHAIN PERFORMANCE - Methods and systems to predict a supply chain performance are described. A system receives supply chain data for delivery of a product. The supply chain data includes input signals comprising operational plans and observed supply chain operational metrics. The input signals include a delivery date of the product. The system automatically generating predicted supply chain operational metrics across including a value at risk that is predicted for the product. The system automatically infers causal factors that impact the predicted supply chain operational metrics including impacting the value at risk that is predicted for the product. The system automatically generates action recommendations for the supply chain. An action recommendation includes a first predicted value impact and a sequence of actions impacting the product the delivery date of the product and the value at risk that is predicted for the product. | 2020-07-02 |
20200210923 | METHOD OF DETERMINING OPTIMAL BUSINESS METRICS FROM A PRODUCT MIX CONSTRAINED BY AT LEAST PHYSICAL SHELF SPACE AND AT LEAST ONE BUSINESS RULE - The present invention relates to a computer implemented method of determining optimal business metrics from a product mix constrained by at least physical shelf space and selectively by at least one business rule. The computer implemented method comprising the steps of defining a boundary constrained shelf space, placing, physically, a product mix within the boundary constrained shelf space, and creating a product mix ranking based, in part, on prior sales of each of the product type. The computer implemented method continues by using a data processing device to develop, through algorithmic autonomous learning, achievable business metric performance of the boundary constrained shelf space. In this regard, a group of similar product mix/ranking is optimized to create an ideal product mix/ranking which is then use to inform changes to make to the product mix to achieve the desired OPTIMAL BUSINESS METRIC. | 2020-07-02 |
20200210924 | ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING BASED INCIDENT MANAGEMENT - In some examples, artificial intelligence and machine learning based incident management may include analyzing incident data related to a plurality of incidents associated with organization operations of an organization to train and test a machine learning classification model. Based on mapping of the organization operations to associated organizational key performance indicators, a corpus may be generated and used to determine an organizational key performance indicator that is impacted by each incident. New incident data related to a further plurality of incidents may be ascertained, and specified organizational key performance indicators associated with further organizational operations may be determined. Based on the corpus and the trained machine learning classification model, an output that includes an organization operation impacted by an incident, and a specified organizational key performance indicator associated with the organizational operation may be determined, and used to control an operation of a system associated with the organization. | 2020-07-02 |
20200210925 | System and method for calculating GRP ratings - A computer-implemented system and method for transparent automated data gathering flow for calculation of Gross Rating Points (GRP) ratings in compliance with European Union General Data Protection Regulation (GDPR) and to provide corresponding transparent EU GDPR compliance GRP rating reports, wherein the GRP ratings are calculated for different types of media on the same panel based on auto generated surveys without human works. The GDPR non-compliance problem in GRP calculation is solved by computer-implemented smart contract procedure using the distributed ledger as decentralized database provided by blockchain platforms supporting smart contract functionality. | 2020-07-02 |
20200210926 | METHOD FOR MANAGING ANNOTATION JOB, APPARATUS AND SYSTEM SUPPORTING THE SAME - A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model. | 2020-07-02 |
20200210927 | OBSERVATION PLATFORM FOR USING STRUCTURED COMMUNICATIONS - In a method of observing users of communication devices, a central computer system recognizes a first user associated with a first communication device and a second user associated with a second communication device. The central computer system observes a communication between the first communication device and the second communication device, wherein at least a portion of the communication is an audible communication. The central computer system relays the communication between the first communication device and the second communication device. The central computer system identifies features of the communication and makes the features available for decision making purposes. | 2020-07-02 |
20200210928 | FLIGHT ATTENDANT EVALUATION SYSTEM AND FLIGHT ATTENDANT EVALUATION METHOD - A system includes a biological sensor measuring biological data of a plurality of customers, a storage storing a plurality of attendant-associated data records, and a processor. Each attendant-associated data record includes the biological data of a customer, a seat identifier, and an attendant identifier associated with each other. The processor calculates at least one stress indicator of at least one customer. Each stress indicator is calculated based on the biological data in one of at least one attendant-associated data record extracted from the plurality of attendant-associated data records and associated with a first attendant identifier. The processor further calculates an evaluation value indicated by the first attendant identifier based on the at least one stress indicator of the at least one customer. The evaluation value is updated based on a registered evaluation value identified by the first attendant identifier stored in the storage, and the calculated stress indicator. | 2020-07-02 |
20200210929 | SEQUENCE MODELING FOR SEARCHES - The disclosed embodiments provide a system for performing sequence modeling for searches. During operation, the system obtains a sequence of jobs associated with activity by a member of an online system. Next, the system applies a word embedding model of a set of job histories to attributes of individual jobs in the sequence of jobs to produce embeddings for the individual jobs. The system then generates a set of power means from the embeddings. Finally, the system outputs the set of power means as an encoded representation of the sequence of jobs, wherein the set of power means is used in generating job recommendations related to the member. | 2020-07-02 |
20200210930 | Method and System for Managing an Event Engaged by a Group of Participants in Real-Time - Embodiments of present disclosure relates to robust and efficient, method and system for managing event engaged by participants in real-time. Initially, input data is received through multiple inputs modes. The input data includes text, audio, image, video, and gesture, associated with event and participants. Further, each participant is profiled, during event. Profiling is based on input data and pre-stored event data associated with event. Behavioural attributes of each participant is indexed based on input data, pre-stored event data and profiling of corresponding participant. Alerts are generated to provide to at least one participant, during event. The alerts are generated based on profiling and indexing of corresponding participant, input data and pre-stored event data. Upon end of event, event data is determined for event and participants, based on profiling, and indexing of participants. By this, event is managed efficiently and dynamically, with real-time alerts and recommendations. | 2020-07-02 |
20200210931 | SYSTEMS AND METHODS FOR SCHEDULING TASKS - Methods, apparatuses, and systems for scheduling tasks to field professionals include: storing, in a database, a plurality of records reflecting characteristics associated with completing a set of technical services, wherein information in each record is derived from historical experience of completing each of the technical services; receiving a request for a new technical service associated with a location; and assigning a field professional to perform the new service having determined from information in the database a likelihood that the field professional will complete the new technical service in a single on-site visit at the location. | 2020-07-02 |
20200210932 | METHODS AND SYSTEMS FOR USING CUSTOMER FEEDBACK IN FUTURE SCHEDULING - Method and systems for scheduling tasks to field professionals include: receiving from a user at least one request for at least one on-site service associated with a location; assigning at least one field professional to at least one task of providing the at least one on-site service at the location; following completion of the at least one on-site service, obtaining data associated with the at least one on-site service; receiving from the user an additional request for an additional service, wherein the additional service is associated with the same location; retrieving information including data associated with the at least one on-site service; and assigning a field professional to perform the additional service based on the retrieved information. | 2020-07-02 |
20200210933 | SYSTEMS AND METHODS FOR SCHEDULING CONNECTED DEVICE - Systems and methods for fixing schedule of tasks using a remote optimization engine are provided. In one implementation, the system may periodically receive from a local server a data associated with a native scheduling engine. The system may process in a stateless manner the data periodically received from the local server using the optimization engine to update a prediction model. The system may also be configured to transmit information associated with the updated prediction model to the local server for enabling improvement of the native scheduling engine. | 2020-07-02 |
20200210934 | ISSUE TRACKING SYSTEM USING A SIMILARITY SCORE TO SUGGEST AND CREATE DUPLICATE ISSUE REQUESTS ACROSS MULTIPLE PROJECTS - An issue tracking system for tracking software development tasks is described herein. The issue tracking system may be configured to receive new issue requests from a client device and associate the new issue requests with one or more clusters of previously stored issue records. The issue tracking system may also determine similarity between issues in a first cluster of stored issue records and issues in a second cluster that is associated with a different software development project. Based on a determination that the issue similarity exceeds a threshold, the user may be prompted with one or more recommendations for a subsequent issue request or issue request content. | 2020-07-02 |
20200210935 | WIRELESS CUSTOMER AND LABOR MANAGEMENT OPTIMIZATION IN RETAIL SETTINGS - Techniques and system configurations for tracking customers and employees in a commercial environment such as a retail store are described herein. Customer devices that are operated by an associated customer may be tracked to determine customer shopping activities in a retail store, and to obtain promotions or affect targeted results based on the customer's activity and a profile associated with the customer. Employee devices that are operated by an associated employee also may be tracked to identify employee activities and manage the interactions that occur with customers in the retail environment. In-store activities and interactions accordingly may be enhanced as a result of advertising, marketing, and analytics derived from the tracked activities. | 2020-07-02 |
20200210936 | SYSTEMS AND METHODS FOR TASK SCHEDULING BASED ON REAL-TIME CONDITIONS - Methods, apparatuses, and systems for scheduling tasks to field professionals include: determining real-time schedule information for field professionals independent from any schedule update received therefrom; determining, from the real-time schedule information associated with a first field professional, existence of a delay associated with tasks assigned to the first field professional; determining a likelihood that the delay will interfere with the first field professional arriving to an identified location associated with an assigned task at a scheduled time; determining from real-time schedule information associated with a second field professional whether the second field professional can arrive to the identified location; reassigning the assigned task based on the real-time schedule information associated with the first field professional and the real-time schedule information associated with the second field professional; and providing to at least one of the first field professional and the second field professional information reflecting the reassignment of the task. | 2020-07-02 |
20200210937 | SYSTEMS AND METHODS FOR FIXING SCHEDULE USING A REMOTE OPTIMIZATION ENGINE - Systems and methods for scheduling tasks to field professionals are provided. In one implementation, the system receives real-time information about a progress of a field professional assigned to a set of tasks. The real-time information may reflect a likelihood the field professional will complete the assigned a set of tasks. The system dynamically determines a window of opportunity to assign an additional task to the field professional based on the real-time information. Thereafter, the system identifies a plurality of optional tasks that the field professional can complete during the window of opportunity. In some cases, the window of opportunity includes an unplanned event likely to interfere with at least one scheduled task. The system can either present the optional tasks to the field professional and assign a task based on the field professional's selection; or automatically select a task for assignment to the field professional based on historical data. | 2020-07-02 |
20200210938 | SYSTEMS AND METHODS FOR FIXING SCHEDULE USING A REMOTE OPTIMIZATION ENGINE - Systems and methods for scheduling tasks to field professionals are provided. In one implementation, the system receives real-time information about a progress of a field professional assigned to a set of tasks. The real-time information may reflect a likelihood the field professional will complete the assigned a set of tasks. The system dynamically determines a window of opportunity to assign an additional task to the field professional based on the real-time information. Thereafter, the system identifies a plurality of optional tasks that the field professional can complete during the window of opportunity. In some cases, the window of opportunity includes an unplanned event likely to interfere with at least one scheduled task. The system can either present the optional tasks to the field professional and assign a task based on the field professional's selection; or automatically select a task for assignment to the field professional based on historical data. | 2020-07-02 |
20200210939 | SYSTEMS AND METHODS FOR ASSIGNING TASKS BASED ON REAL-TIME CONDITIONS - Systems and methods for fixing schedule of tasks using a remote optimization engine are provided. In one implementation, the system may periodically receive from a local server a data associated with a native scheduling engine. The system may process in a stateless manner the data periodically received from the local server using the optimization engine to update a prediction model. The system may also be configured to transmit information associated with the updated prediction model to the local server for enabling improvement of the native scheduling engine. | 2020-07-02 |
20200210940 | Selecting Project Resources based on Resource Characteristics and Role Correlations - An approach is provided in which an information handling system computes work role correlation values corresponding to work role pairs that each includes a pair of work roles corresponding to a project. The information handling system groups resources corresponding to the work roles into resource sets, each of which including a unique set of resources. Next, the information handling system computes resource set scores for each of the resource sets based on their respective unique set of resources and the work role correlation values. In turn, the information handling system selects one of the resource sets based on the resource set scores. | 2020-07-02 |