USPTO Patent Grant: Automatic Experience Research with User Personalization
Summary
The USPTO has granted patent US12586094B2 to Yahoo Assets LLC for a method and apparatus for automatic experience research with user personalization. The patent covers techniques for optimizing user response by comparing a global-best user experience variant against a machine model trained on user data to identify a user-preferred variant.
What changed
The United States Patent and Trademark Office (USPTO) has granted patent US12586094B2, titled 'Automatic experience research with a user personalization option method and apparatus,' to Yahoo Assets LLC. This patent covers novel techniques for evaluating user experience experiments, specifically focusing on optimizing user response by comparing a predetermined 'global-best' user experience variant against a machine learning model trained to predict user preferences. The system aims to recommend whether to adopt the global-best variant or the machine model's prediction for delivering user experiences.
This patent grant is primarily relevant to technology companies involved in user experience research, A/B testing, and personalized content delivery. While it does not impose direct compliance obligations on regulated entities, it represents a new intellectual property asset in the field of AI-driven user experience optimization. Companies developing or utilizing similar technologies should be aware of this patent's claims, particularly concerning the comparison of aggregate user responses and machine model predictions for user experience selection. No specific compliance deadlines or penalties are associated with this patent grant itself, but infringement could lead to legal action by the patent holder.
Source document (simplified)
Automatic experience research with a user personalization option method and apparatus
Grant US12586094B2 Kind: B2 Mar 24, 2026
Assignee
YAHOO ASSETS LLC
Inventors
Guruganesh Kotta, Michael Natkovich, Mahendrasinh Jadav, Miao Chen, Chandrashekhar Shaw, Rahul Kapoor
Abstract
Techniques for evaluating a user experience experiment designed to use one user experience variant selected from a number of user experience variants as a global-best user experience variant to be used across users relative to a machine model trained to use user data to identify a user-preferred user experience variant. Disclosed systems and methods provide techniques for optimizing user response. In one embodiment, a global-best user experience variant is evaluated by comparing an aggregate user response determined for the global-best user experience variant to an aggregate user response determined using user response predictions determined using the trained machine model, and using the outcome of the comparison to make a recommendation as to which one of the global-best user experience variant and the trained machine model to adopt for providing a user experience to users.
CPC Classifications
G06Q 30/0203 G06Q 30/0282 G06N 20/00
Filing Date
2021-12-06
Application No.
17542642
Claims
20
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