Research on cross-border e-commerce recommendation system based on collaborative filtering

Zijian Li

doi:10.1117/12.2671183

1 June 2023 Research on cross-border e-commerce recommendation system based on collaborative filtering

Zijian Li

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 1262510 (2023) https://doi.org/10.1117/12.2671183
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

In the modern economic innovation and development, cross-border e-commerce as a new business industry, the actual data scale began to expand sharply as e-commerce, system users are faced with information overload and other problems, so researchers put forward to develop a corresponding recommendation system. Nowadays, when studying the recommendation system of cross-border e-commerce, scholars from various countries not only put forward a variety of recommendation system models, but also achieved excellent results in practice and exploration. Since cross-border e-commerce contains entry and exit information of multiple types of commodities, it will be affected by various policies and regulations, and the special needs of recommendation systems need to be comprehensively considered. Therefore, the traditional collaborative filtering recommendation algorithm does not meet the needs of e-commerce industry in the new era. On the basis of understanding the research status of cross-border e-commerce recommendation system in recent years, this paper deeply discusses the structure of cross-border e-commerce promotion system based on collaborative filtering according to the basic concept of collaborative filtering algorithm. The final experimental results show that the improved collaborative filtering algorithm has more application value and good recommendation effect than the traditional collaborative filtering algorithm.

Citation Download Citation

Zijian Li "Research on cross-border e-commerce recommendation system based on collaborative filtering", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 1262510 (1 June 2023); https://doi.org/10.1117/12.2671183

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