Improved Pre-Processing Stages in Web Usage Mining Using Web Log

Enormous growth in the web persists both in number of web sites and number of users. The growth generated large volume of data in during user’s interaction with the web site and recorded in web logs. Web site owners need to understand about their users by accessing these web logs. Web mining perks up to comprehend range of concepts of diverse fields. Web Usage Mining (WUM) is the recent research field that it corresponds to the process of Knowledge Discovery in Databases (KDD). It comprises three main categories: Pre-Processing, Pattern Analysis, Pattern Discovery. WUM extracts behavioral data from web users data and if possible from web site information (structure and content). In this paper, we propose a customized application specific methodology for preprocessing the Web logs and combining WUM with Association Rule Mining