摘要：随着全球化的发展，跨境电子商务成为了一个重要的商业模式。在跨境电子商务中，商品推荐系统是提高用户购物体验和促进销售的重要手段。本文提出了一种基于深度学习算法的B2C跨境电子商务商品推荐系统，该系统采用了卷积神经网络和循环神经网络相结合的方法，能够对用户的历史购买记录和浏览记录进行分析，从而为用户推荐最符合其需求的商品。实验结果表明，该系统能够有效提高商品推荐的准确性和用户购物体验。
关键词：深度学习；跨境电子商务；商品推荐；卷积神经网络；循环神经网络
Abstract: With the development of globalization, cross-border e-commerce has become an important business model. In cross-border e-commerce, the product recommendation system is an important means to improve the user shopping experience and promote sales. This paper proposes a B2C cross-border e-commerce product recommendation system based on deep learning algorithms. The system uses a combination of convolutional neural networks and recurrent neural networks to analyze users' historical purchase and browsing records, and recommend the most suitable products for users. The experimental results show that the system can effectively improve the accuracy of product recommendations and user shopping experience.
Keywords: Deep learning; Cross-border e-commerce; Product recommendation; Convolutional neural network; Recurrent neural network
基于深度学习算法的B2C跨境电子商务商品推荐系统构建及应用
