Research on Cross-Border E-Commerce Recommendation System Based on Deep Learning Algorithm

Abstract

With the rapid development of science and technology, people's shopping methods have also undergone qualitative changes, e-commerce is the most important way, compared with physical stores, e-commerce goods are more diverse. Cross-border e-commerce is a very important part of e-commerce, which allows people to buy products from other countries. E-commerce recommendations are very important to allow people to buy the products they want. The ordinary recommendation model cannot solve the problem of e-commerce recommendation accuracy in cross-border e-commerce, and the evaluation is unreasonable. Therefore, this paper proposes a cross-border e-commerce recommendation system for e-commerce recommendation analysis. In the tide of digital economy, cross-border electronic commerce has developed rapidly with its borderless business opportunities and convenient trading mode. However, with the proliferation of product types and the increasingly prominent personalized needs of users, how to accurately recommend products to potential buyers has become a key problem to be solved urgently for e-commerce platforms.