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

Yang Liu; Fei Lei

doi:10.1117/12.3045477

20 September 2024 Design and simulation of cross-border e-commerce customer profile processing system based on improved genetic algorithm

Yang Liu, Fei Lei

Author Affiliations +

Proceedings Volume 13269, Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024); 132690Y (2024) https://doi.org/10.1117/12.3045477
Event: Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yang Liu and Fei Lei "Design and simulation of cross-border e-commerce customer profile processing system based on improved genetic algorithm", Proc. SPIE 13269, Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024), 132690Y (20 September 2024); https://doi.org/10.1117/12.3045477

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