Personalized Commodity Recommendation Using A Multi-Stage Algorithm


The KIPS Transactions:PartD, Vol. 10, No. 7, pp. 1225-1230, Dec. 2003
10.3745/KIPSTD.2003.10.7.1225,   PDF Download:

Abstract

Many cyber-shopping malls use various commodity recommendation methods. Although the detailed algorithms are not disclosed to the public, they mostly rely on relatively simple and straightforward methods. This paper intends to improve the commodity recommendation by using a multi-stage algorithm which considers factors that are characteristics of the commodity itself, of the consumer group, and of the individual customer. A comparison table is provided which shows whether there is a change in commodity recommendation as we consider more factors about the customer.


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Cite this article
[IEEE Style]
J. B. Cheol, C. D. Won, L. D. Cheol, "Personalized Commodity Recommendation Using A Multi-Stage Algorithm," The KIPS Transactions:PartD, vol. 10, no. 7, pp. 1225-1230, 2003. DOI: 10.3745/KIPSTD.2003.10.7.1225.

[ACM Style]
Jang Byeong Cheol, Choe Deog Won, and Lee Dong Cheol. 2003. Personalized Commodity Recommendation Using A Multi-Stage Algorithm. The KIPS Transactions:PartD, 10, 7, (2003), 1225-1230. DOI: 10.3745/KIPSTD.2003.10.7.1225.