Research on E-commerce Content Recommendation System Based on Fuzzy ART
Download as PDF
Guo Xin, Xiao Min
With the popularity of the Internet and the improvement of people's needs, the problem of information overload corresponding to e-commerce is very prominent. In this context, an effective e-commerce recommendation system is developed to provide personalized recommendation services for users, so as to provide service guarantee for users to find the products they need. The wide application of recommendation system provides good technical support for convenient life, but there are many problems and challenges behind the rise of this technology. To improve these problems is to promote the development of recommendation system towards a more humane direction. On this basis, this paper focuses on the research of e-commerce content recommendation system based on Fuzzy ART, which provides basic ideas for the optimization of commodity recommendation services.
Fuzzy ART, E-commerce, Recommendation System, Recommendation Algorithms