Abstract
The rapid growth of e-commerce had caused product overload where customers were no longer able to effectively choose the products that they were needed.To meet the personalized needs of customers in E- supermarket, the technologies of web usage mining, collaborative filtering and decision tree were applied in the paper, while a new personalized recommendation algorithm were proposed. Personalized recommendation algorithm were also used in personalized recommendation service system based on E-supermarket (PRSSES). The results manifest that it could support E-commerce better. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Feng, X., & Luo, Q. (2007). Research on personalized recommendation algorithm in E-supermarket system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4537 LNCS, pp. 340–347). Springer Verlag. https://doi.org/10.1007/978-3-540-72909-9_38
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