Patents by Inventor Joseph Allen Notter

Joseph Allen Notter has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Methods, systems and computer readable media for predicting risk in network elements using machine learning
    Patent number: 11337087
    Abstract: A method, system and computer-readable medium where a weighted composite quality index having a plurality of components for a network element is identified. A historical baseline value from historical data for each component is determined, and a deviation from the historical baseline values is measured. A risk level for the deviation is assigned. A loss score for the measured components is computed by mapping the risk level to a numerical score. An aggregated risk score based on a sum of weighted risk scores for each of the components is computed. An expected risk score based on probabilities associated with the aggregated risk score is determined by computing future probabilities of each risk level at the network element based on a trained machine learning model.
    Type: Grant
    Filed: February 27, 2020
    Date of Patent: May 17, 2022
    Assignees: AT&T Intellectual Property I, L.P., AT&T Mobility II LLC
    Inventors: Supratim Deb, He Yan, Karunasish Biswas, Joseph Allen Notter
  • Methods, Systems and Computer Readable Media for Predicting Risk in Network Elements Using Machine Learning
    Publication number: 20200367078
    Abstract: A method, system and computer-readable medium where a weighted composite quality index having a plurality of components for a network element is identified. A historical baseline value from historical data for each component is determined, and a deviation from the historical baseline values is measured. A risk level for the deviation is assigned. A loss score for the measured components is computed by mapping the risk level to a numerical score. An aggregated risk score based on a sum of weighted risk scores for each of the components is computed. An expected risk score based on probabilities associated with the aggregated risk score is determined by computing future probabilities of each risk level at the network element based on a trained machine learning model.
    Type: Application
    Filed: February 27, 2020
    Publication date: November 19, 2020
    Inventors: Supratim Deb, He Yan, Karunasish Biswas, Joseph Allen Notter
  • Methods, systems and computer readable media for predicting risk in network elements using machine learning
    Patent number: 10609578
    Abstract: A method, system and computer-readable medium where a weighted composite quality index having a plurality of components for a network element is identified. A historical baseline value from historical data for each component is determined, and a deviation from the historical baseline values is measured. A risk level for the deviation is assigned. A loss score for the measured components is computed by mapping the risk level to a numerical score. An aggregated risk score based on a sum of weighted risk scores for each of the components is computed. An expected risk score based on probabilities associated with the aggregated risk score is determined by computing future probabilities of each risk level at the network element based on a trained machine learning model.
    Type: Grant
    Filed: May 16, 2019
    Date of Patent: March 31, 2020
    Assignees: AT&T Intellectual Property I, L.P., AT&T Mobility II LLC
    Inventors: Supratim Deb, He Yan, Karunasish Biswas, Joseph Allen Notter