The variable precision rough set model for web usage mining

Abstract

Web Knowledge Discovery and Data Mining includes discovery and leveraging different kinds of hidden patterns in web data. In this paper we mine web user access patterns and classify users using the Variable Precision Rough Set (VPRS) model. Certain user sessions of web access are positive examples and other sessions are negative examples. Cumulative graphs capture all known positive example sessions and negative example sessions. They are then used to identify the attributes that are used to form an equivalence relation. This equivalence relation is used for the β-probabilistic approximation classification of the VPRS model. An illustrative experiment is presented.