Patents by Inventor Ramkrishna Soma

Ramkrishna Soma 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).

  • SYSTEMS AND METHODS FOR MACHINE LEARNING MODELS FOR SEARCH ENGINE PERFORMANCE OPTIMIZATION
    Publication number: 20230244726
    Abstract: Methods, systems, and computer-readable media for updating a machine learning model utilized in a search engine operation. The method identifies a set of search queries in stored search queries corresponding to a service and apply the identified set of search queries to the search engine to generate one or more search results for the service. Each search result has an assigned aggregate based on values of a set of parameters associated with the service. The method then analyzes the values of the set of parameters to determine a tradeoff point of each parameter to determine one or more weights to apply to the machine learning model based on the tradeoff points. The method stores the determined one or more weights and applies them to the machine learning model for a search query corresponding to the service.
    Type: Application
    Filed: April 7, 2023
    Publication date: August 3, 2023
    Applicant: Included Health, Inc.
    Inventors: Nathaniel Freese, Derek Macklin, Ramkrishna Soma, Eric Carlson, Stephen Martin
  • Systems and methods for machine learning models for search engine performance optimization
    Patent number: 11640435
    Abstract: Methods, systems, and computer-readable media for updating a machine learning model utilized in a search engine operation. The method identifies a set of search queries in stored search queries corresponding to a service and apply the identified set of search queries to the search engine to generate one or more search results for the service. Each search result has an assigned aggregate based on values of a set of parameters associated with the service. The method then analyzes the values of the set of parameters to determine a tradeoff point of each parameter to determine one or more weights to apply to the machine learning model based on the tradeoff points. The method stores the determined one or more weights and applies them to the machine learning model for a search query corresponding to the service.
    Type: Grant
    Filed: January 31, 2022
    Date of Patent: May 2, 2023
    Assignee: INCLUDED HEALTH, INC.
    Inventors: Nathaniel Freese, Derek Macklin, Ramkrishna Soma, Eric Carlson, Stephen Martin
  • SYSTEMS AND METHODS FOR MACHINE LEARNING MODELS FOR SEARCH ENGINE PERFORMANCE OPTIMIZATION
    Publication number: 20220156333
    Abstract: Methods, systems, and computer-readable media for updating a machine learning model utilized in a search engine operation. The method identifies a set of search queries in stored search queries corresponding to a service and apply the identified set of search queries to the search engine to generate one or more search results for the service. Each search result has an assigned aggregate based on values of a set of parameters associated with the service. The method then analyzes the values of the set of parameters to determine a tradeoff point of each parameter to determine one or more weights to apply to the machine learning model based on the tradeoff points. The method stores the determined one or more weights and applies them to the machine learning model for a search query corresponding to the service.
    Type: Application
    Filed: January 31, 2022
    Publication date: May 19, 2022
    Applicant: Grand Rounds, Inc.
    Inventors: Nathaniel Freese, Derek Macklin, Ramkrishna Soma, Eric Carlson, Steven Martin
  • Systems and methods for machine learning models for search engine performance optimization
    Patent number: 11238113
    Abstract: Methods, systems, and computer-readable media for updating a machine learning model utilized in a search engine operation. The method identifies a set of search queries in stored search queries corresponding to a service and apply the identified set of search queries to the search engine to generate one or more search results for the service. Each search result has an assigned aggregate based on values of a set of parameters associated with the service. The method then analyzes the values of the set of parameters to determine a tradeoff point of each parameter to determine one or more weights to apply to the machine learning model based on the tradeoff points. The method stores the determined one or more weights and applies them to the machine learning model for a search query corresponding to the service.
    Type: Grant
    Filed: March 29, 2021
    Date of Patent: February 1, 2022
    Assignee: Grand Rounds Inc.
    Inventors: Nathaniel Freese, Derek Macklin, Ramkrishna Soma, Eric Carlson, Steven Martin
  • SYSTEMS AND METHODS FOR MACHINE LEARNING MODELS FOR SEARCH ENGINE PERFORMANCE OPTIMIZATION
    Publication number: 20210311999
    Abstract: Methods, systems, and computer-readable media for updating a machine learning model utilized in a search engine operation. The method identifies a set of search queries in stored search queries corresponding to a service and apply the identified set of search queries to the search engine to generate one or more search results for the service. Each search result has an assigned aggregate based on values of a set of parameters associated with the service. The method then analyzes the values of the set of parameters to determine a tradeoff point of each parameter to determine one or more weights to apply to the machine learning model based on the tradeoff points. The method stores the determined one or more weights and applies them to the machine learning model for a search query corresponding to the service.
    Type: Application
    Filed: March 29, 2021
    Publication date: October 7, 2021
    Applicant: Grand Rounds, Inc.
    Inventors: Nathaniel Freese, Derek Macklin, Ramkrishna Soma, Eric Carlson, Steven Martin