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

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 1. Introduction With the development of information technology and the widespread use of the internet, the way people access information has undergone profound changes. Faced with an overwhelming amount of information, quickly obtaining information that matches personal interests and needs has become a significant challenge for users.