Patents Examined by Alan Chen
  • Patent number: 11120336
    Abstract: According to an exemplary embodiment of the present disclosure, disclosed is a computer program stored in a computer readable storage medium. When the computer program is executed in one or more processors, the computer program performs the following method for anomaly detection of data using a network function, and the method includes: generating an anomaly detection model including a plurality of anomaly detection sub models including a trained network function using a plurality of training data sub sets included in the training data set; calculating input data using at least one of the plurality of generated anomaly detection sub models; and determining whether there is an anomaly in the input data based on output data for input data of at least one of the plurality of generated anomaly detection sub models and the input data.
    Type: Grant
    Filed: September 10, 2020
    Date of Patent: September 14, 2021
    Assignee: MAKINAROCKS CO., LTD.
    Inventors: Andre S. Yoon, Yongsub Lim, Sangwoo Shim
  • Patent number: 11113608
    Abstract: Implementations are directed to receiving communication data from a device, the communication data including data input by a user of the device, determining a context based on an extended finite state machine that defines contexts and transitions between contexts, transmitting a service request to at least one cloud-hosted service, the service request being provided at least partially based on masking sensitive information included in the communication data, receiving a service response from the at least one cloud-hosted service, the service response including one or more of an intent, and an entity, determining at least one action that is to be performed by at least one back-end source system based on the service response, providing a response at least partially based on an action results received from the at least one back-end source system, and transmitting the result data to the device.
    Type: Grant
    Filed: October 30, 2017
    Date of Patent: September 7, 2021
    Assignee: Accenture Global Solutions Limited
    Inventors: Tariq Mohammad Salameh, Michele Tornielli
  • Patent number: 11113628
    Abstract: A problem context is computed from an input at an application. The problem context includes a set of problem factors, the input including a problem to be solved using a cognitive system. A user context is computed from the input at the application, the user context including a set of user factors. A type of media is determined corresponding to a complexity of a cognitive solution received from the cognitive system, where the cognitive solution is in response to the problem. Using a problem factor from the set of problem factors, using a user factor in the set of user factors, and the complexity, a mode of communication is determined. A communication apparatus is adjusted to cause a data communication to occur and deliver the cognitive solution in the type of media using the mode of communication.
    Type: Grant
    Filed: December 21, 2017
    Date of Patent: September 7, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Peter C. Bahrs, Paul K. Bullis, Geoffrey M. Hambrick
  • Patent number: 11113626
    Abstract: A problem context is computed from an input at an application. The problem context includes a set of problem factors, the input including a problem to be solved using a cognitive system. A user context is computed from the input at the application, the user context including a set of user factors. A type of media is determined corresponding to a complexity of a cognitive solution received from the cognitive system, where the cognitive solution is in response to the problem. Using a problem factor from the set of problem factors, using a user factor in the set of user factors, and the complexity, a mode of communication is determined. A communication apparatus is adjusted to cause a data communication to occur and deliver the cognitive solution in the type of media using the mode of communication.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: September 7, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Peter C. Bahrs, Paul K. Bullis, Geoffrey M. Hambrick
  • Patent number: 11106986
    Abstract: Systems and methods for implementing and using a data modeling and machine learning lifecycle management platform that facilitates collaboration among data engineering, development and operations teams and provides capabilities to experiment using different models in a production environment to accelerate the innovation cycle. Stored computer instructions and processors instantiate various modules of the platform. The modules include a user interface, a collector module for accessing various data sources, a workflow module for processing data received from the data sources, a training module for executing stored computer instructions to train one or more data analytics models using the processed data, a predictor module for producing predictive datasets based on the data analytics models, and a challenger module for executing multi-sample hypothesis testing of the data analytics models.
    Type: Grant
    Filed: February 24, 2020
    Date of Patent: August 31, 2021
    Assignee: DataTron Technologies Inc.
    Inventors: Harish Doddi, Jerry Xu
  • Patent number: 11106981
    Abstract: A method, system and computer-usable medium for using cognitive graph vectors to refine cognitive insights comprising storing data from a plurality of data sources within a cognitive graph via a cognitive inference and learning system; associating a first set of the data within the cognitive graph with a first cognitive graph vector of a plurality of cognitive graph vectors via the cognitive inference and learning system; associating a second set of the data within the cognitive graph with a second cognitive graph vector of the plurality of cognitive graph vectors via the cognitive inference and learning system; processing the data from the plurality of data sources to provide cognitive insights via the cognitive inference and learning system; and refining the cognitive insights based upon a limitation relating to one of the plurality of cognitive graph vectors via the cognitive inference and learning system.
    Type: Grant
    Filed: May 17, 2018
    Date of Patent: August 31, 2021
    Assignee: Cognitive Scale, Inc.
    Inventor: Matthew Sanchez
  • Patent number: 11100387
    Abstract: Systems and methods for predicting are described herein. A record for each of a plurality of events associated with user transactions can be stored. A sequential plurality of the events can be analyzed using a unidirectional long short term memory (LSTM) and first and second dense neural network layers configured to receive output from the LSTM network.
    Type: Grant
    Filed: May 7, 2018
    Date of Patent: August 24, 2021
    Assignee: The Boston Consulting Group, Inc.
    Inventors: Arun Karthik Ravindran, Vincent Francois Faber, Jack Chua
  • Patent number: 11100396
    Abstract: Self-adjusting thresholds for synaptic activity in neural networks are provided. In various embodiments, for each of a plurality of neurons within an artificial neural network, an overlap value is determined corresponding to active inputs connected to the neuron via synapses having non-zero synaptic weights. A count of those of the plurality of neurons whose overlap exceeds an activation threshold of the neural network is determined. The count is compared to a predetermined neuronal activity target. The activation threshold of the neural network is adjusted to approach the predetermined neuronal activity target.
    Type: Grant
    Filed: August 24, 2017
    Date of Patent: August 24, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Ahmet S. Ozcan, J. Campbell Scott
  • Patent number: 11100425
    Abstract: Systems, computer-implemented methods and/or computer program products that facilitate automatically mapping different data types are provided. In one embodiment, a computer-implemented method comprises: constructing, by a system operatively coupled to a processor, an index from one or more classifier models for one or more data types; scoring and ranking, by the system, one or more candidate pairs for the one or more data types based on confidence score; and analyzing, by the system, how the one or more candidate pairs are scored and automatically generating the one or more classifier models used to construct the index.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: August 24, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jian Min Jiang, Pei Ni Liu, Yuan Ni, Wen Sun, Guo Tong Xie, Jing Min Xu
  • Patent number: 11100399
    Abstract: Systems and methods for training a neural network model are disclosed. In the method, training data is obtained by a deep neural network (DNN) first, the deep neural network comprising at least one hidden layer. Then features of the training data are obtained from a specified hidden layer of the at least one hidden layer, the specified hidden layer being connected respectively to a supervised classification network for classification tasks and an autoencoder based reconstruction network for reconstruction tasks. And at last the DNN, the supervised classification network and the reconstruction network are trained as a whole based on the obtained features, the training being guided by the classification tasks and the reconstruction tasks.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: August 24, 2021
    Assignee: International Business Machines Corporation
    Inventors: Wei Shan Dong, Peng Gao, Chang Sheng Li, Chun Yang Ma, Kai AD Yang, Ren Jie Yao, Ting Yuan, Jun Zhu
  • Patent number: 11100153
    Abstract: A computing server may receive master data, transaction data, and one or more existing process models of a domain. The computing server may aggregate, based on domain knowledge ontology of the domain, the master data and the transaction data to generate a fact table. For example, entries in the fact table may be identified as relevant to the target process model and include attributes and facts that are extracted from master data or transaction data. The computing server may convert the entries in the fact table into vectors. The computing server inputting vectors into one or more machine learning algorithms to generate one or more algorithm outputs. One or more algorithm outputs may correspond to one or more improved process models that are optimized compared to the existing process models. The computing server may provide the improved process model to the domain to replace one of the existing process models.
    Type: Grant
    Filed: May 28, 2020
    Date of Patent: August 24, 2021
    Assignee: Zuora, Inc.
    Inventors: Sudipto Shankar Dasgupta, Michael Reh
  • Patent number: 11089437
    Abstract: Sensor data having values received from several sensors of a mobile device and response data associated with the sensor data may be used in the determination or training of a predictive model. Received sensor data may be input into the predictive model, and the output of the predictive model may be used in the selection and serving of content items to the mobile device. Data to effect presentation of the selected content item may be outputted to the mobile device to effect presentation. In some instances, the predictive model may be updated using the received plurality of values. The updated predictive model may be used in the selection of a subsequent content item for the mobile device. In other implementations, historical sensor data may be used with the set of received sensor data as input for the predictive model.
    Type: Grant
    Filed: August 21, 2018
    Date of Patent: August 10, 2021
    Assignee: Google LLC
    Inventors: Lukasz Bieniasz-Krzywiec, Dariusz Leniowski, Venu Vemula
  • Patent number: 11080720
    Abstract: Systems and methods generate a risk score for an account event. The systems and methods automatically generate a causal model corresponding to a user, wherein the model estimates components of the causal model using event parameters of a previous event undertaken by the user in an account of the user. The systems and methods predict expected behavior of the user during a next event in the account using the causal model. Predicting the expected behavior of the user includes generating expected event parameters of the next event. The systems and methods use a predictive fraud model to generate fraud event parameters. Generation of the fraud event parameters assumes a fraudster is conducting the next event, wherein the fraudster is any person other than the user. The systems and methods generate a risk score of the next event to indicate the relative likelihood the future event is performed by the user.
    Type: Grant
    Filed: September 25, 2018
    Date of Patent: August 3, 2021
    Assignee: GUARDIAN ANALYTICS, INC.
    Inventor: Tom Miltonberger
  • Patent number: 11080592
    Abstract: A neuromorphic architecture for a spiking neural network comprising a plurality of spiking neurons, each with a plurality of synapses and corresponding synaptic weights, the architecture further comprising a synaptic competition mechanism in connection with a spike-based learning mechanism based on spikes perceived behind a synapse, in which architecture synapses of different neurons connected to the same input compete for that input and based on the result of that competition, each neuron of the neural network develops an individual perception of the presented input spikes, the perception used by the learning mechanism to adjust the synaptic weights.
    Type: Grant
    Filed: October 5, 2017
    Date of Patent: August 3, 2021
    Assignee: International Business Machines Corporation
    Inventors: Stanislaw A. Wozniak, Angeliki Pantazi
  • Patent number: 11074927
    Abstract: A computer implemented method, computer system and computer program product are provided for acoustic event detection in polyphonic acoustic data, according to the method, polyphonic acoustic data is inputted by one or more processing units into a trained neural network trained by labeled monophonic acoustic data, a first output from a hidden layer of the trained neural network is obtained by one or more processing units, and at least one acoustic classification of the polyphonic acoustic data is determined by one or more processing units based on the first output and a feature dictionary learnt from the trained neural network.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: July 27, 2021
    Assignee: International Business Machines Corporation
    Inventors: Xiao Xing Liang, Ning Zhang, Yu Ling Zheng, Yu Chen Zhou
  • Patent number: 11068793
    Abstract: An inference device disclosed herein includes an identifying unit, and an inferring unit. The identifying unit identifies a set of a predetermined phenomenon, an effect having a causal relation with the predetermined phenomenon, and a polarity of the effect, from concept information in which a phenomenon, an effect having a causal relation with the phenomenon, a polarity to be an indicator of advantages and disadvantages caused by the effect to a user. The inferring unit infers an effect caused when the predetermined phenomenon occurs, and advantages and disadvantages caused by the effect based on the set identified by the identifying unit.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: July 20, 2021
    Assignee: YAHOO JAPAN CORPORATION
    Inventor: Ikuo Kitagishi
  • Patent number: 11062207
    Abstract: Data indicative of a plurality of observations of an environment are received at a control system. Machine learning using deep reinforcement learning is applied to determine an action based on the observations. The deep reinforcement learning applies a convolutional neural network or a deep auto encoder to the observations and applies a training set to locate one or more regions having a higher reward. The action is applied to the environment. A reward token indicative of alignment between the action and a desired result is received. A policy parameter of the control system is updated based on the reward token. The updated policy parameter is applied to determine a subsequent action responsive to a subsequent observation.
    Type: Grant
    Filed: October 30, 2017
    Date of Patent: July 13, 2021
    Assignee: RAYTHEON TECHNOLOGIES CORPORATION
    Inventors: Michael J. Giering, Kishore K. Reddy, Vivek Venugopalan, Amit Surana, Soumalya Sarkar
  • Patent number: 11057399
    Abstract: An information processing device according to the present invention includes: a dissimilarity calculator that calculates dissimilarity that is a distance between already received first alert information, and newly received second alert information; a machine learning generator that generates a classifier by applying machine learning to the first alert information, and determines a classification result by applying the classifier to the second alert information; and a determiner that sets the determination result and information indicating that presentation is unnecessary for the second alert information, when the determination result is false detection and the dissimilarity is less than a threshold value, and sets information indicating that presentation is necessary for the second alert information, when the determination result is true detection, or when the determination result is false detection and the dissimilarity is equal to or more than a threshold value.
    Type: Grant
    Filed: June 15, 2016
    Date of Patent: July 6, 2021
    Assignee: NEC CORPORATION
    Inventor: Satoshi Ikeda
  • Patent number: 11049027
    Abstract: A method for providing a visual summary of a plurality of answers associated with a question entered into a natural language question answer system by a user is provided. The method may include receiving the entered question. The method may also include analyzing the entered question to determine a plurality of possible answers to the entered question. The method may further include compiling a set of answers based on the analysis of the entered question and the determined plurality of possible answers. The method may additionally include providing a characterization summary for the compiled set of answers, whereby the characterization summary includes an indication of the quality associated with each answer within the compiled set of answers.
    Type: Grant
    Filed: March 30, 2018
    Date of Patent: June 29, 2021
    Assignee: International Business Machines Corporation
    Inventors: Sean G. Jalleh, Amanda C. Maderic, Andrew Patrick Mankins, David L. Schwartz, Lila Title
  • Patent number: 11049016
    Abstract: A circuit for performing neural network computations for a neural network comprising a plurality of neural network layers, the circuit comprising: a matrix computation unit configured to, for each of the plurality of neural network layers: receive a plurality of weight inputs and a plurality of activation inputs for the neural network layer, and generate a plurality of accumulated values based on the plurality of weight inputs and the plurality of activation inputs; and a vector computation unit communicatively coupled to the matrix computation unit and configured to, for each of the plurality of neural network layers: apply an activation function to each accumulated value generated by the matrix computation unit to generate a plurality of activated values for the neural network layer.
    Type: Grant
    Filed: March 19, 2020
    Date of Patent: June 29, 2021
    Assignee: Google LLC
    Inventors: Jonathan Ross, Norman Paul Jouppi, Andrew Everett Phelps, Reginald Clifford Young, Thomas Norrie, Gregory Michael Thorson, Dan Luu