Microsoft patents method to predict clicks using summarized context
Microsoft describes a system that predicts how likely a user is to click on a piece of content by analyzing both the item and its surrounding context. The method converts text into numerical data, simplifies the context information, and combines it with the main item to estimate click probability.
In the filing’s own words
The present disclosure proposes content recommendation based on embedding summarization. A text input may be obtained, the text input including a basic input and a context input, the basic input including a candidate content item. An embedding sequence corresponding to the basic input and an embedding sequence corresponding to the context input may be generated. A pooling embedding may be generated through performing a pooling operation on the embedding sequence corresponding to the basic input. A representative embedding sequence corresponding to the context input may be obtained through performing a summary operation on the embedding sequence corresponding to the context input. A text input representation of the text input may be generated based on the embedding sequence corresponding to the basic input and the representative embedding sequence. A click probability of the candidate content item being clicked may be predicted based on the text input representation.
What exactly they claim (claim 1)
1. A method for content recommendation based on embedding summarization, comprising: obtaining a text input, the text input including a basic input and a context input corresponding to the basic input, the basic input including at least a candidate content item; generating an embedding sequence corresponding to the basic input and an embedding sequence corresponding to the context input; generating a pooling embedding corresponding to the basic input through performing a pooling operation on the embedding sequence corresponding to the basic input; obtaining a representative embedding sequence corresponding to the context input through performing a summary operation on the embedding sequence corresponding to the context input with the pooling embedding; generating a text input representation of the text input based at least on the embedding sequence corresponding to the basic input and the representative embedding sequence corresponding to the context input; and predicting a click probability of the candidate content item being clicked based on the text input representation.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- CONTENT RECOMMENDATION BASED ON EMBEDDING SUMMARIZATION
- Publication number
- US20260267894A1
- Application number
- 18876837
- Filed
- Jul 14, 2023
- Published
- Sep 10, 2026
- Inventors
- 5
- Claims
- 15
Classified under
G06F 16/335 Physics & computingG06F 16/345 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.