Research and Implementation of E-commerce Intelligent Recommendation System Based on Fuzzy Clustering Algorithm

The rapid development of e-commerce has brought about the problem of information overload, and users may encounter uninterested content and even online fraud when browsing. How to effectively filter such information and intelligently recommend desirable products to users has become the core research direction of this article. The article is divided into four parts: the first part analyzes the current situation of intelligent recommendation technology and elaborates on the research ideas; The second part introduces the principles and processes of commonly used collaborative filtering algorithms and fuzzy clustering algorithms used in experiments, analyzes the drawbacks of traditional collaborative filtering algorithms, and explains the practical applicability of fuzzy clustering algorithms; The third part presents an intelligent recommendation system based on fuzzy clustering, which integrates user and product characteristics, and uses user evaluations to achieve intelligent recommendations based on content and collaborative filtering. At the end of the article, comparative experiments are conducted to highlight the advantages of the e-commerce intelligent recommendation system based on fuzzy clustering algorithm in improving recommendation accuracy.