Patents by Inventor Thomas Lomont

Thomas Lomont 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).

  • Patent number: 12086726
    Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.
    Type: Grant
    Filed: September 13, 2022
    Date of Patent: September 10, 2024
    Assignee: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Thomas Lomont, Sen Yang, Siyang Li, John Ingraham
  • Publication number: 20230267177
    Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.
    Type: Application
    Filed: January 6, 2023
    Publication date: August 24, 2023
    Applicant: Mastercard International Incorporated
    Inventors: Thomas Lomont, Sen Yang, Siyang Li, John Ingraham
  • Patent number: 11551024
    Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.
    Type: Grant
    Filed: November 22, 2019
    Date of Patent: January 10, 2023
    Assignee: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Thomas Lomont, Sen Yang, Siyang Li, John Ingraham
  • Publication number: 20230004842
    Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.
    Type: Application
    Filed: September 13, 2022
    Publication date: January 5, 2023
    Applicant: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Thomas Lomont, Sen Yang, Siyang Li, John Ingraham
  • Patent number: 11443203
    Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.
    Type: Grant
    Filed: November 22, 2019
    Date of Patent: September 13, 2022
    Assignee: MASTERCARD INTERNATIONAL INCORPORATED
    Inventors: Thomas Lomont, Sen Yang, Siyang Li, John Ingraham