Patents by Inventor F. Jay Breyer

F. Jay Breyer 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 automatically assessing constructed recommendations based on sentiment and specificity measures
    Patent number: 10515153
    Abstract: A computer-implemented method of training an assessment model for assessing constructed texts expressing opinions on subjects includes accessing a plurality of training texts, which are constructed texts. The training texts are analyzed with the processing system to derive values of a plurality of linguistic features of an assessment model. At least one of the plurality of linguistic features relates to sentiment and at least one of the plurality of linguistic feature relates to specificity. The assessment model is trained with the processing system based on the values of the plurality of linguistic features. Based on the training, a weight for each of the plurality of linguistic features is determined. The assessment model is calibrated to include the weights for at least some of the plurality of linguistic features such that the assessment model is configured to generate assessment measures for constructed texts expressing opinions on subjects.
    Type: Grant
    Filed: May 16, 2014
    Date of Patent: December 24, 2019
    Assignee: Educational Testing Service
    Inventors: Michael Heilman, F. Jay Breyer, Michael Flor
  • Systems and Methods for Assessing Constructed Recommendations
    Publication number: 20140343923
    Abstract: A computer-implemented method of training an assessment model for assessing constructed texts expressing opinions on subjects includes accessing a plurality of training texts, which are constructed texts. The training texts are analyzed with the processing system to derive values of a plurality of linguistic features of an assessment model. At least one of the plurality of linguistic features relates to sentiment and at least one of the plurality of linguistic feature relates to specificity. The assessment model is trained with the processing system based on the values of the plurality of linguistic features. Based on the training, a weight for each of the plurality of linguistic features is determined. The assessment model is calibrated to include the weights for at least some of the plurality of linguistic features such that the assessment model is configured to generate assessment measures for constructed texts expressing opinions on subjects.
    Type: Application
    Filed: May 16, 2014
    Publication date: November 20, 2014
    Applicant: Educational Testing Service
    Inventors: Michael Heilman, F. Jay Breyer, Michael Flor