Title: Investigation on cross-border electronic commerce recommendation algorithm based on data mining and computer network

Authors: Dan Jiang

Addresses: Economics and Management School, Jingchu University of Technology, Jingmen, 448000, Hubei, China

Abstract: In recent years, the rapid development of cross-border electronic commerce (CBEC) has become a new type of electronic commerce, and its data scale has grown rapidly in synchronisation with the development of electronic commerce. Currently, Chinas traditional foreign trade is at a stage of insufficient growth and continuous downturn, and its upgrading cycle is too long. In the marketing of CBEC, due to various reasons, there are specific requirements for recommendation algorithms for CBEC, which makes traditional recommendation algorithms unable to accurately predict user purchasing. This paper combined data mining (DM) with the theory of CBEC recommendation algorithms in computer networks (CN) and recommendation systems, and compared them from three perspectives: click rate, traffic conversion rate, and user retention rate. The experimental results showed that, from the perspective of click rate, the average click rate based on traditional filtering algorithms was 10.2.

Keywords: CBEC; cross-border electronic commerce; data mining; computer networks; association analysis mining algorithm.

DOI: 10.1504/IJNVO.2025.151026

International Journal of Networking and Virtual Organisations, 2025 Vol.33 No.2, pp.167 - 186

Received: 21 Apr 2025
Accepted: 03 Nov 2025
Published online: 09 Jan 2026 *

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