Patents Examined by Alan Chen
  • Patent number: 10332012
    Abstract: Various embodiments of systems and methods to provide a knowledge driven solution inference are described herein. In one aspect, unstructured data is retrieved from one or more information sources. Data segments corresponding to a plurality of categories are identified in the extracted unstructured data by natural language processing. Further, the data segments are grouped into a plurality of data clusters based on scores between the data segments. The structured knowledge base is generated by linking the associated plurality of data clusters. The knowledge driven solution inference is provided based on the generated knowledge base.
    Type: Grant
    Filed: October 8, 2015
    Date of Patent: June 25, 2019
    Assignee: SAP SE
    Inventor: Srinivasa Byaiah Ramachandra Reddy
  • Patent number: 10332122
    Abstract: A user's physiological status is monitored and the resulting physiological status data is obtained and analyzed to determine whether a user would benefit from user support intervention. If it is determined that the user would benefit from intervention, an intervention notification is provided to a user support service. The user support service may then provide dynamic and responsive user support. To provide effective, efficient user support, different types of user support can be provided to the user.
    Type: Grant
    Filed: July 27, 2015
    Date of Patent: June 25, 2019
    Assignee: Intuit Inc.
    Inventors: Garron Engstrom, Amir Eftekhari, Ann Catherine Jose, Erik Kaasila, Konstantin Gizdarski
  • Patent number: 10325271
    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: October 13, 2014
    Date of Patent: June 18, 2019
    Assignee: Guardian Analytics, Inc.
    Inventor: Tom Miltonberger
  • Patent number: 10325213
    Abstract: A cognitive learning method comprising: receiving data from a plurality of data sources; processing the data from the plurality of data sources to perform a cognitive learning operation, the processing being performed via a cognitive inference and learning system, the cognitive learning operation comprising a plurality of cognitive learning operation lifecycle phases, the cognitive learning operation applying a cognitive learning technique to generate a cognitive learning result; and, updating a destination based upon the cognitive learning result.
    Type: Grant
    Filed: September 29, 2015
    Date of Patent: June 18, 2019
    Assignee: Cognitive Scale, Inc
    Inventors: Matthew Sanchez, Manoj Saxena
  • Patent number: 10318879
    Abstract: A method for providing an interactive interface for live event outcome selection and prediction may include generating a set of cells for an event. The set of cells may be provided to a client device to present in a user interface. A selection of a cell may be received from the client device. The selected cell may be assigned to a user account. The method may generate a coordinate for each cell in the set, wherein each cell coordinate includes a plurality of dimensions, each dimension corresponding to a different entity of the event, and wherein each cell coordinate is unique for the set of cells. The method may comprise calculating, prior to the start of the event, a probability that an event result represented by a cell coordinate will occur; and presenting the probability in association with the cell on the user interface. Other embodiments are described and claimed.
    Type: Grant
    Filed: October 30, 2015
    Date of Patent: June 11, 2019
    Assignee: CBS Interactive Inc.
    Inventors: Leonard Michael Lopez, Carlos Javier Carbonell Di Mola, Raymond Solebello, Christian J Soblotne, Patrick Mark Quinlivan
  • Patent number: 10318864
    Abstract: A deep learning network is trained to automatically analyze enterprise data. Raw data from one or more global data sources is received, and a specific training dataset that includes data exemplary of the enterprise data is also received. The raw data from the global data sources is used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario. The specific training dataset is then used to further train the deep learning network to predict the results of a specific enterprise outcome scenario. Alternately, the raw data from the global data sources may be automatically mined to identify semantic relationships there-within, and the identified semantic relationships may be used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario.
    Type: Grant
    Filed: July 24, 2015
    Date of Patent: June 11, 2019
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Li Deng, Jianfeng Gao, Xiaodong He, Prabhdeep Singh
  • Patent number: 10318869
    Abstract: A decision-making process is implemented by a decider processing unit. The decision-making process includes the propagation of a proposition in a distributed network of processing units, with each processing unit being provided with decision intelligence.
    Type: Grant
    Filed: January 7, 2014
    Date of Patent: June 11, 2019
    Assignee: AIRBUS DS SAS
    Inventors: Christopher Rabotin, Fabien Valverde
  • Patent number: 10318876
    Abstract: Embodiments of the present invention provide systems and methods for increasing the quality of interactions between two or more entities. These entities are either individuals (e.g., human beings using a computer device) or artificial intelligence (AI) agents. The interactions between all of the entities within a computing environment are mapped and analyzed. Based on the mapped interactions, a relationship model is generated in order to run multiple applications within a computing environment.
    Type: Grant
    Filed: May 25, 2017
    Date of Patent: June 11, 2019
    Assignee: International Business Machines Corporation
    Inventors: Aaron K. Baughman, Diwesh Pandey, John P. Perrino, Todd R. Whitman
  • Patent number: 10311363
    Abstract: A method comprises processing metagenomics sequencing results from a plurality of metagenomics sequencing centers associated with respective data zones, configuring a data model based at least in part on the metagenomics sequencing results, performing one or more reasoning operations over the data model to infer relationships between entities of the data model that are not directly expressed by the data model, and updating the data model based at least in part on the inferred relationships. The method further comprises repeating the processing, configuring, performing and updating for additional metagenomics sequencing results from one or more of the metagenomics sequencing centers. One or more portions of the data model illustratively comprise respective profiles each characterizing at least one of a disease, infection or contamination based at least in part on the metagenomics sequencing results.
    Type: Grant
    Filed: December 30, 2015
    Date of Patent: June 4, 2019
    Assignee: EMC IP Holding Company LLC
    Inventors: Patricia Gomes Soares Florissi, Michal Ziv Ukelson, Ran Dach, Arnon Benshahar
  • Patent number: 10296835
    Abstract: 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.
    Type: Grant
    Filed: June 6, 2014
    Date of Patent: May 21, 2019
    Assignee: Intel Corporation
    Inventor: Amit S. Baxi
  • Patent number: 10289955
    Abstract: Systems and methods for predicting virality of a content item are disclosed. A method includes: receiving a social network structure; identifying communities within the social network structure, where communities are identified as dense subnetworks in the social network structure; receiving social network content that includes one or more content items; and identifying one or more content items that are predicted to become viral based on utilization of the content items between different communities in the social network structure.
    Type: Grant
    Filed: March 12, 2014
    Date of Patent: May 14, 2019
    Assignee: Indiana University Research and Technology Corporation
    Inventors: Filippo Menczer, Lilian Weng, Yong Yeol Ahn, Jr.
  • Patent number: 10289949
    Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.
    Type: Grant
    Filed: September 29, 2015
    Date of Patent: May 14, 2019
    Assignee: International Business Machines Corporation
    Inventors: Aaron K. Baughman, Christian Eggenberger, Andrea I. Martin, Daniel S. Stoessel, Craig M. Trim
  • Patent number: 10282665
    Abstract: There is provided an information processing apparatus including a reward estimator generator using action history data, including state data expressing a state, action data expressing an action taken by an agent, and a reward value expressing a reward obtained as a result of the action, as learning data to generate, through machine learning, a reward estimator estimating a reward value from inputted state data and action data. The reward estimator generator includes: a basis function generator generating a plurality of basis functions; a feature amount vector calculator calculating feature amount vectors by inputting state data and action data in the action history data into the basis functions; and an estimation function calculator calculating an estimation function estimating the reward value included in the action history data from the feature amount vectors according to regressive/discriminative learning. The reward estimator includes the plurality of basis functions and the estimation function.
    Type: Grant
    Filed: June 12, 2015
    Date of Patent: May 7, 2019
    Assignee: SONY CORPORATION
    Inventor: Yoshiyuki Kobayashi
  • Patent number: 10275720
    Abstract: A processing node in a temporal memory system includes a spatial pooler and a sequence processor. The spatial pooler generates a spatial pooler signal representing similarity between received spatial patterns in an input signal and stored co-occurrence patterns. The spatial pooler signal is represented by a combination of elements that are active or inactive. Each co-occurrence pattern is mapped to different subsets of elements of an input signal. The spatial pooler signal is fed to a sequence processor receiving and processed to learn, recognize and predict temporal sequences in the input signal. The sequence processor includes one or more columns, each column including one or more cells. A subset of columns may be selected by the spatial pooler signal, causing one or more cells in these columns to activate.
    Type: Grant
    Filed: October 9, 2015
    Date of Patent: April 30, 2019
    Assignee: NUMENTA, INC.
    Inventors: Jeffrey C. Hawkins, Ronald Marianetti, II, Anosh Raj, Subutai Ahmad
  • Patent number: 10268958
    Abstract: A technology is described for providing a recommended launch configuration for a computing instance based on a predicted launch time. An example method may include receiving a launch plan to launch a computing instance on a physical host within a computing service environment, where the launch plan includes a launch configuration. Upon receiving the launch plan, a predicted launch time may be determined for the computing instance based on the launch configuration. The launch configuration may then be analyzed to identify changes to the launch configuration that may result in an improved predicted launch time as compared to the predicted launch time. A recommended change may then be provided for the launch configuration as a result of a determination that the change to the launch configuration results in the improved predicted launch time.
    Type: Grant
    Filed: September 10, 2014
    Date of Patent: April 23, 2019
    Assignee: Amazon Technologies, Inc.
    Inventors: Anton André Eicher, Matthew James Eddey, Richard Alan Hamman
  • Patent number: 10268951
    Abstract: A generated algorithm used by a neural network is captured during execution of an iteration of the neural network. A candidate algorithm is identified based on the generated algorithm. A determination is made that the candidate algorithm utilizes less memory than the generated algorithm. Based on the determination the neural network is updated by replacing the generated algorithm with the candidate algorithm.
    Type: Grant
    Filed: June 14, 2017
    Date of Patent: April 23, 2019
    Assignee: International Business Machines Corporation
    Inventors: Taro Sekiyama, Kiyokuni Kawachiya, Tung D. Le, Yasushi Negishi
  • Patent number: 10262262
    Abstract: The present invention relates to the technical field of terminal devices of the Internet of Things, more specifically to a semantic method for terminal devices of the Internet of Things capable of analyzing the application characteristics of terminal devices of the Internet of Things, setting down the rules for building ontology base; analyzing and building initial ontology base by using the ontology base building tool; pre-processing information from network and sensors; collecting information uploaded by sensors, updating the initial ontology base, and expanding the ontology base by collecting information searched by network. The method establishes program plan by object-oriented mode, analyzes implementing results by using existing test data or simulated data, and realizes domain updating and expansion of sensor ontology according to specific applications. The whole development and evolution of sensor ontology is increasing gradually in a spiral form.
    Type: Grant
    Filed: December 20, 2013
    Date of Patent: April 16, 2019
    Assignee: SHENYANG INSTITUTE OF AUTOMATION OF THE CHINESE ACADEMY OF SCIENCES
    Inventors: Xing Tong, Yang Liu, Zhao Shi, Peng Zeng, Haibin Yu
  • Patent number: 10262260
    Abstract: Systems and methods for training networks are provided. A method for training networks comprises receiving an input from each of a plurality of neural networks differing from each other in at least one of architecture, input modality, and feature type, connecting the plurality of neural networks through a common output layer, or through one or more common hidden layers and a common output layer to result in a joint network, and training the joint network.
    Type: Grant
    Filed: February 16, 2017
    Date of Patent: April 16, 2019
    Assignee: International Business Machines Corporation
    Inventors: George A. Saon, Hagen Soltau
  • Patent number: 10262271
    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 14, 2018
    Date of Patent: April 16, 2019
    Assignee: DataTron Technologies Inc.
    Inventors: Harish Doddi, Jerry Xu
  • Patent number: 10242756
    Abstract: Various systems and methods for predicting metabolic and bariatric surgery outcomes are provided. The systems and methods can also provide predictions for non-surgical metabolic and bariatric treatments. In general, a user can receive predictive outcomes of multiple bariatric procedures that could be performed on a patient. In one embodiment, a user can electronically access a metabolic and bariatric surgery outcome prediction system, e.g., using one or more web pages. The system can provide predictive outcomes of one or more different bariatric surgeries for the patient based on data gathered from the user and on historical data regarding outcomes of the different bariatric surgeries. The system can additionally provide predictive outcomes for not having any treatment and/or a comparison of the predictive outcomes of the one or more different bariatric surgeries to the predictive outcomes for not having any treatment.
    Type: Grant
    Filed: December 29, 2015
    Date of Patent: March 26, 2019
    Assignee: Ethicon Endo-Surgery, Inc.
    Inventors: Jason L. Harris, Christopher J. Hess, Nitin Kumar Jain, Diane M. Francis, Thomas E. Albrecht, Tina Denise Hunter