Microsoft patents system that learns which content users prefer over time
Microsoft describes a method for selecting digital content, such as ads or articles, by using machine learning to predict what users will find rewarding. The system starts with an initial guess, measures how well different choices perform based on user feedback, and then updates its model to make better selections for future requests.
In the filing’s own words
A method involves first receiving a set of data on rewards associated with previously chosen content variant choices, selected based on an initial content variant choice model. This initial model is informed by a prior set of data. A second, updated content variant choice model is then determined based on this first set of reward data. When a request for selecting a content variant choice is received, it comes with contextual features. The method involves estimating the expected rewards for a range of content variant choices, considering these contextual features. Subsequently, a specific content variant choice is chosen based on both the updated model and the anticipated rewards. Finally, the chosen content variant is displayed on a device, responding to the initial request.
What exactly they claim (claim 1)
1. A method, comprising: generating a first output using a first machine learning-based model based on context data and choice data of a first training data item; generating a second output using a second machine learning-based model, wherein the second output comprises an output sampled from a distribution generated based on the first output and reward data of the first training data item; generating a loss function output using a loss function based on the second output and the reward data of the first training data item; and updating the first machine learning-based model based on the loss function output.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- CONTEXTUAL LONG-TERM SURVIVAL OPTIMIZATION FOR CONTENT MANAGEMENT SYSTEM CONTENT SELECTION
- Publication number
- US20260311208A1
- Application number
- 19468606
- Filed
- Feb 3, 2026
- Published
- Oct 8, 2026
- Inventors
- 8
- Claims
- 20
Classified under
G06Q 30/0236 Physics & computingMore from Microsoft in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.