Microsoft patents ad system that guesses who is browsing a page
This filing describes a method for a content delivery server to guess which user is requesting a web page by calculating the probability of different user identities. It then uses a mathematical function to pick the most likely user profile, allowing the server to choose specific content, such as an advertisement, based on that user's known attributes.
In the filing’s own words
Machine learning (ML) and probabilistic techniques for identification and content delivery are described. A method comprises receiving, by a content delivery server, a request from a web server for content. The server then determines a set of user-probability pairs, each pair including a predicted user identifier and a probability that the predicted user identifier is associated with the request from the web server. The method further includes applying an objective function to the set of user-probability pairs to select one of the user identifiers with a corresponding candidate user profile. Based on the selected user identifier, a content item is selected for delivery to the web server.
What exactly they claim (claim 1)
1. A method comprising: receiving, by a content delivery server, a request from a web server for content; determining, by the content delivery server, a set of user-probability pairs, wherein each of the user-probability pairs includes a predicted user identifier and a probability that the predicted user identifier is associated with the request from the web server, and wherein each pair in the set of user-probability pairs includes an attribution value associated therewith; applying, by the content delivery server, an objective function to the set of user-probability pairs to select one user identifier of the set of user identifiers with a corresponding candidate user profile, wherein applying the objective function comprises: in a first selection, selecting, by the content delivery server, a random user identifier; or in a second selection, selecting, by the content delivery server, the user identifier having a greatest attribution value associated therewith; wherein the content delivery server is configured to make a decision to execute the first selection or the second selection based on a selection parameter; accessing, by the content delivery server, the corresponding candidate user profile of the selected user identifier to determine a set of attributes of the corresponding candidate user profile; selecting, by the content delivery server and based on the request and the set of attributes, a content item from a plurality of content item options to be sent to the web server; and causing, by the content delivery server, the content item to be sent to the web server.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- TECHNIQUES FOR PROBABILISTIC IDENTIFICATION FOR CONTENT DELIVERY
- Publication number
- US20260267931A1
- Application number
- 19073420
- Filed
- Mar 7, 2025
- Published
- Sep 10, 2026
- Inventors
- 5
- Claims
- 20
Classified under
G06F 16/9535 Physics & computingG06F 16/9035 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.