Research and Application of E-Commerce Recommendation System Based on Association Rules Algorithm

摘要

With the advent of the information age, online shopping has become an integral part of people's lives, but how to help users quickly and effectively choose the product is a big challenge. This paper puts forward the system structure of e-commerce recommendation system, and combines it with the association rules algorithm to reduce the time and space cost of e-commerce recommendation system in practical application. Its innovation is to use the characteristics of association rules, through the analysis of the user's previous data to recommend the user needs. At last, this paper compares the performance gap between the Apriori algorithm and the FP-Growth algorithm, and further improves the value of electronic commerce recommendation system.