Kye Sun An, Se Jin Go, Jun Jiong, Phill Kyu Rhee

The KIPS Transactions:PartB , Vol. 9, No. 4, pp. 389-398, Aug. 2002
10.3745/KIPSTB.2002.9.4.389,   PDF Download:

Abstract

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially, a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Apriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

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