Patents by Inventor Clement Jacques Antoine TUSSOIT

Clement Jacques Antoine TUSSOIT 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: 11301766
    Abstract: A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.
    Type: Grant
    Filed: December 22, 2020
    Date of Patent: April 12, 2022
    Assignee: salesforce.com, inc.
    Inventors: Kristen Noriko Muramoto, Son Thanh Chang, Clement Jacques Antoine Tussoit, Melissa Hoang, Chaitanya Malla, Orjan N. Kjellberg, Carlos Enrique Mogollan Jimenez, George Hu
  • Publication number: 20210182716
    Abstract: A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.
    Type: Application
    Filed: December 22, 2020
    Publication date: June 17, 2021
    Applicant: salesforce.com, inc.
    Inventors: Kristen Noriko Muramoto, Son Thanh Chang, Clement Jacques Antoine Tussoit, Melissa Hoang, Chaitanya Malla, Orjan N. Kjellberg, Carlos Enrique Mogollan Jimenez, George Hu
  • Patent number: 10915827
    Abstract: A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.
    Type: Grant
    Filed: November 21, 2018
    Date of Patent: February 9, 2021
    Assignee: salesforce.com, inc.
    Inventors: Kristen Noriko Muramoto, Son Thanh Chang, Clement Jacques Antoine Tussoit, Melissa Hoang, Chaitanya Malla, Orjan N. Kjellberg, Carlos Enrique Mogollan Jimenez, George Hu
  • Publication number: 20200097846
    Abstract: A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.
    Type: Application
    Filed: November 21, 2018
    Publication date: March 26, 2020
    Inventors: Kristen Noriko MURAMOTO, Son Thanh CHANG, Clement Jacques Antoine TUSSOIT, Melissa HOANG, Chaitanya MALLA, Orjan N. Kjellberg, Carlos Enrique Mogollan JIMENEZ, George HU