Data Analysis of Cross-Border E-Commerce Entrepreneurship Based on User Portraits

This paper proposes a transnational e-commerce platform based on user portrait. The system adopts Spring Mvc+ spring+ mybatis architecture. Using MySQL5.7 database, Tomcat7.0 server, redis cache and other methods, customers and merchants are seamlessly connected to provide prototypes. A method based on "word frequency-text frequency-tag weight" is proposed to model business records of a large number of customers in cross-border e-commerce enterprises. This project establishes a personalized marking system based on customer portraits to conduct in-depth research on the customer service activities of multinational e-commerce enterprises. We tap into the hidden high-risk information and present it to consumers. Practice has proved that dangerous behaviors can be found effectively by modeling user characteristics in the network, which help cross-border e-commerce to achieve data security operation dynamic monitoring. Based on word frequency statistics, the algorithm based on word frequency and PDF is convenient for statistics and calculation, and it is used to calculate the E-mail text frequency. In the project, we propose a clustering algorithm based on user behavior, which can extract user interest model from raw data. Through the analysis of user behavior, we can better understand the user's behavior pattern. And through the understanding of users, we discover the potential needs of users, which can provide valuable services for enterprises.