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Web usage mining (WUM) is an important and fast developing area of web mining. Recently, some enterprises have been aware of its potentials, especially for applications in Business Intelligence (BI) and Customer Relationship Management (CRM). Therefore, it is crucial to analyze the behaviors and characteristics of web user so as to use this knowledge for advertising, targeted marketing, increasing competition ability, etc. This paper provides an analytic method, algorithm and procedure based on suggestions from literature and the authors' experiences from some practical web mining projects. Its application shows combined use of frequent sequence patterns (FSP) discovery and the characteristic analysis of user clusters can contribute to improve and optimize marketing and CRM.

The Characteristic Analysis of Web User Clusters Based on Frequent Browsing Patterns