Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866912071734525952 |
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| author | Mao, Chunyan Huang, Shuaishuai Sui, Mingxiu Yang, Haowei Wang, Xueshe |
| author_facet | Mao, Chunyan Huang, Shuaishuai Sui, Mingxiu Yang, Haowei Wang, Xueshe |
| contents | With the rapid development of the internet and the explosion of information, providing users with accurate personalized recommendations has become an important research topic. This paper designs and analyzes a personalized recommendation system based on a dynamic user interest model. The system captures user behavior data, constructs a dynamic user interest model, and combines multiple recommendation algorithms to provide personalized content to users. The research results show that this system significantly improves recommendation accuracy and user satisfaction. This paper discusses the system's architecture design, algorithm implementation, and experimental results in detail and explores future research directions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_09923 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model Mao, Chunyan Huang, Shuaishuai Sui, Mingxiu Yang, Haowei Wang, Xueshe Information Retrieval Artificial Intelligence With the rapid development of the internet and the explosion of information, providing users with accurate personalized recommendations has become an important research topic. This paper designs and analyzes a personalized recommendation system based on a dynamic user interest model. The system captures user behavior data, constructs a dynamic user interest model, and combines multiple recommendation algorithms to provide personalized content to users. The research results show that this system significantly improves recommendation accuracy and user satisfaction. This paper discusses the system's architecture design, algorithm implementation, and experimental results in detail and explores future research directions. |
| title | Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model |
| topic | Information Retrieval Artificial Intelligence |
| url | https://arxiv.org/abs/2410.09923 |