A stochastic model of e-customer behavior

摘要

Web usage mining techniques are increasingly used today to understand e-customers’ within-site behavior. We propose a data mining model that considers e-customers’ activities as a discrete-time semi-Markov process and explains their behavior. An algorithm is proposed to compute transition probability matrix and holding time mass functions from the site navigation data. Finally, the model is used to explain customer behavior in an example site. A software agent, implemented in the site, collects and stores navigation data in the required form and thus helps to avoid data preprocessing. The model results helped to improve the site design and judge its performance.