Design and simulation of cross-border e-commerce customer profile processing system based on improved genetic algorithm

This article proposes a cross-border e-commerce customer file processing system based on an improved genetic algorithm. The system utilizes improved genetic algorithms and big data technology of artificial intelligence to process and analyze cross-border e-commerce customer data, create customer profiles, and provide personalized services and recommendations for enterprises. It also introduces more advanced machine learning technology to improve the system's ability to predict and identify customer needs, thereby providing more accurate and diverse personalized recommendation services. This article provides a detailed introduction to the design and implementation process of the system, and conducts simulation experiments. The results indicate that the system can effectively process cross-border e-commerce customer data and generate accurate customer profiles. Therefore, a more precise and accurate understanding of customers becomes the key for cross-border e-commerce enterprises to build core competitive advantages.