E-Commerce Intelligent Recommendation System Based on Deep Learning

Abstract

With the popularity of smart phones, e-commerce has developed rapidly. Intelligent recommendation is a very important task in the field of e-commerce. Researchers have proposed the use of association rules, collaborative filtering, Markov chain, recurrent neural network and other technologies for shopping basket recommendation. This paper mainly studies e-commerce intelligent recommendation system(IRS) based on deep learning. In this paper, the overall design of e-commerce recommendation system is firstly carried out, and the functional modules and system architecture of e-commerce IRS are proposed. Then, this paper discusses the recommendation algorithm in the e-commerce IRS, and optimizes the e-commerce IRS based on convolutional neural network. Finally, this paper compares and analyzes the performance of three popular recommendation algorithms on Alibaba data set. Experimental results show that the proposed convolutional neural network recommendation algorithm based on deep learning is superior to the other two algorithms and has strong practical significance and promotion value.