Mining traveling and purchasing behaviors of customers in electronic commerce environment

Abstract

Web usage mining is the process of extracting interesting patterns from Web logs. We propose an IPA (integrating path traversal patterns and association rules) model for Web usage mining in the EC (electronic commerce) environment. The IPA model takes both the traveling and purchasing behaviors of customers into consideration at the same time to overcome the disadvantages of the pure association rule mining and pure path traversal pattern mining. The IPA model considers not only user traversal forward information but also backward information. Besides, Web structure is also used to prune unnecessary candidates. Especially, the IPA model allows the noise exist in Web transactions. The experimental results show that the IPA model can correctly capture the user's traversing and purchasing behaviors.