Modeling and application of implicit feedback in personalized recommender systems
Traditional recommendation algorithms usually rely on the user's existing data and historical behavioral records to make recommendations, which often leads to low recommendation accuracy and insufficient personalized experience. To solve these problems, this paper proposes an innovative recomme...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2025-03-01
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| Series: | Electronic Research Archive |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/era.2025053 |
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