内容推荐方法、装置、设备及计算机可读存储介质
By analyzing users' historical access sequences and content features, and optimizing content recommendation using content index and Faiss index, the problem of low recommendation efficiency in existing technologies is solved, achieving more efficient and accurate content recommendation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TENCENT TECHNOLOGY (SHENZHEN) CO LTD
- Filing Date
- 2021-04-19
- Publication Date
- 2026-07-17
AI Technical Summary
Existing content recommendation methods struggle to accurately identify the content to be recommended, resulting in low recommendation efficiency and making it difficult for users to find content of interest from massive amounts of information.
By obtaining the target user's historical access sequence and content characteristics, user behavior characteristics are determined. Content similar to user behavior characteristics is recommended using a content index library. The calculation is optimized by combining the Faiss index library and incorporating semantic features of different attributes to obtain the content to be recommended.
It improves the accuracy and efficiency of content recommendation, reduces the operational pressure on the recommendation service, avoids problems such as content duplication and large computational load, and enhances the user experience.
Smart Images
Figure CN115221392B_ABST