Goods Recommendation System using a Customer`s Preference Features Information


The KIPS Transactions:PartD, Vol. 11, No. 5, pp. 1205-1212, Oct. 2004
10.3745/KIPSTD.2004.11.5.1205,   PDF Download:

Abstract

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of adaptive e-commerce agents can monitor customer's behaviors and cluster them in similar categories, and include user's preference from each category. In order to implement our adaptive e-commerce agent system, in this paper, we propose an adaptive e-commerce agent systems consider customer's information of interest and goodwill ratio about preference goods. Proposed system build user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile. The proposed system composed with three parts ; Monitor Agent which grasps user's intension using monitoring, similarity reference Agent which refers to similar group of behavior pattern after learned behavior pattern of user, Interest Analyzing Agent which personalized behavior DB as a change of user's behavior.


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Cite this article
[IEEE Style]
K. S. Sung, Y. C. Park, J. M. Ahn, H. S. Oh, "Goods Recommendation System using a Customer`s Preference Features Information," The KIPS Transactions:PartD, vol. 11, no. 5, pp. 1205-1212, 2004. DOI: 10.3745/KIPSTD.2004.11.5.1205.

[ACM Style]
Kyung Sang Sung, Yeon Chool Park, Jae Myung Ahn, and Hae Seok Oh. 2004. Goods Recommendation System using a Customer`s Preference Features Information. The KIPS Transactions:PartD, 11, 5, (2004), 1205-1212. DOI: 10.3745/KIPSTD.2004.11.5.1205.