Abstract
The rapid development of computer network technology makes the electronic shopping come into fashion. In this paper, first we analyze the common electronic shopping system and discuss the bottlenecks that restrict its development. To solve these problems, individual product information should be provided to customers. Then we propose a Bayesian customer model and apply it in our intelligent electronic shopping system, which can predict the requirements of customers and provide them with individual product information actively.
The work is supported by the Natural Science Foundation of China (NSFC), Beijing Municipal Natural Science Foundation (BMNSF) and Chinese 863 High-Tech Program.
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© 2001 Springer-Verlag Berlin Heidelberg
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Ji, J., Zheng, L., Liu, C. (2001). The Intelligent Electronic Shopping System Based on Bayesian Customer Modeling. In: Zhong, N., Yao, Y., Liu, J., Ohsuga, S. (eds) Web Intelligence: Research and Development. WI 2001. Lecture Notes in Computer Science(), vol 2198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45490-X_74
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DOI: https://doi.org/10.1007/3-540-45490-X_74
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