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  4. Vol 8, Issue 5, 2024

Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model

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DOI: 10.23977/acss.2024.080513 | Downloads: 58 | Views: 1167

Author(s)

Chunyan Mao 1, Shuaishuai Huang 2, Mingxiu Sui 3, Haowei Yang 4, Xueshe Wang 5

Affiliation(s)

1 School of Information and Communication Engineering, Shanghai Jiao Tong University, Shanghai, China
2 Department of Software, University of Science and Technology of China, Software System Design, Hefei, Anhui, China
3 Department of Mathematics, University of Iowa, Iowa City, Iowa, USA
4 Cullen College of Engineering, University of Houston, Indusrial Enginnering, Houston, TX, USA
5 Pratt School of Engineering, Duke University, Mechanical Engineering, Durham, NC, USA

Corresponding Author

Chunyan Mao

ABSTRACT

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.

KEYWORDS

Personalized Recommendation System; Dynamic User Interest Model; Recommendation Algorithm; User Behavior Data; System Design

CITE THIS PAPER

Chunyan Mao, Shuaishuai Huang, Mingxiu Sui, Haowei Yang, Xueshe Wang, Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model. Advances in Computer, Signals and Systems (2024) Vol. 8: 109-118. DOI: http://dx.doi.org/10.23977/acss.2024.080513.

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