ABSTRACT

Web usage mining has assumed importance in learning about web user's behavior and user interactions with the website. It uses data mining techniques to discover non-trivial user behavior patterns. These patterns can then be used to make the predictions of next page to be accessed by the user. Web usage mining consists of the steps like web log preprocessing, pattern discovery and pattern analysis. This paper proposes a novel approach for preprocessing wherein rough set clustering is applied to form the clusters of sessions. These sessions could later on be used to form the knowledge base of rules on the basis of which the next page to be accessed could be prefetched.