The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 14, 2023

Filed:

Apr. 24, 2023
Applicant:

Wevo, Inc., Boston, MA (US);

Inventors:

Dustin Garvey, Exeter, NH (US);

Janet Muto, Boston, MA (US);

Nitzan Shaer, Newton, MA (US);

Shannon Walsh, Boston, MA (US);

Alexa Stewart, Andover, MA (US);

Andrea Paola Aguilera Garcia, Cambridge, MA (US);

Kim Coccoluto, Wakefield, MA (US);

Sara Peters, Syracuse, NY (US);

Ruthie McCready, Austin, TX (US);

Kelly Lyons, Boston, MA (US);

Melany Carvalho, Pawtucket, RI (US);

Everett Granger, Virginia Beach, VA (US);

Julia McCarthy, Boston, MA (US);

Frank Chiang, Boston, MA (US);

Alexander Barza, Cambridge, MA (US);

Hannah Sieber, Mendon, MA (US);

Assignee:

Wevo, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01);
Abstract

Techniques are described for producing machine learning models to generate findings associated with user experiences with products and/or services. In some embodiments, a training process receives a set of findings from one or more user experience tests, where a finding includes a summary and a set of one or more references supporting the summary. The training process further identifies a supplemental set of one or more references that were not included in the initial finding to support the summary. The training process trains a machine learning model, such as a neural or generative language model, based on the first set of one or more references and the second set of one or more references to generate summaries from a subset of sampled references based at least in part on the first set of one or more references and the second set of one or more references.


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