Artificial intelligence based theme builder for processing user expectations

US12165193B2 · kind B2 · utility

Assignee

• Wevo, Inc · US

Inventors

• Dustin Garvey · Oakland, US
• Shannon Walsh · Boston, US
• Frank Chiang · Boston, US
• Janet Muto · Boston, US
• Nitzan Shaer · Boston, US
• Charlie Hoang · Boston, US
• Hannah Sieber · Mendon, US
• Nick Montaquila · Boston, US
• Jessica Yau · Quincy, US
• Joseph Gibson · Alpharetta, US
• Mary McMurray · Pinehurst, US
• Laurie Delaney · Dedham, US
• Andrea Paola Aguilera García · Cambridge, US
• Alexa Stewart · Andover, US

Key dates

• Filing date: Nov 4, 2022
• Grant date: Dec 10, 2024
• Expiry date: Nov 25, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/0203
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.