Content recommendation method, apparatus, device, computer-readable storage medium, and product
By establishing a replacement resource library in the content recommendation system and replacing low-quality content with high-quality resources, the problem of poor content recommendation quality in existing technologies is solved, and higher-quality content recommendation is achieved.
CN115757945BActive Publication Date: 2026-07-21BAIDU COM TIMES TECH (BEIJING) CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BAIDU COM TIMES TECH (BEIJING) CO LTD
- Filing Date
- 2022-11-15
- Publication Date
- 2026-07-21
AI Technical Summary
Technical Problem
Existing content recommendation methods contain a lot of duplicate, copied, and non-original content, resulting in poor recommended content quality and a poor user experience.
Method used
Establish a replacement resource library, which includes multiple sets of replacement resource pairs. Each set consists of two similar resources with different content quality. Replace low-quality content in the recommended content list with replacement resources to form a target recommendation list.
Benefits of technology
It improves the quality of recommended content, enhances user experience, and ensures the originality and clarity of recommended content.
✦ Generated by Eureka AI based on patent content.
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Figure CN115757945B_ABST
Abstract
The present disclosure provides a content recommendation method, device, equipment, computer readable storage medium and product, relates to the field of data processing, and particularly relates to the field of big data. The specific implementation scheme is as follows: a recommendation content list corresponding to a target user is acquired, wherein the recommendation content list comprises identification information of a plurality of recommendation contents; according to the identification information of the plurality of recommendation contents, a plurality of replacement resources associated with the recommendation content list are determined in a preset replacement resource library, the replacement resource library comprises a plurality of replacement resource pairs, and each replacement resource pair comprises two similar resources with different content qualities; the recommendation contents in the recommendation content list that match the replacement resources are replaced by the replacement resource pairs to obtain a target recommendation list; and a content recommendation operation is performed on the target user according to the target recommendation list. Thus, the content with poor quality in the recommendation content list can be replaced, the quality of the recommendation content is effectively improved, and the user experience is improved.
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