An effective data preprocessing method for Web Usage Mining

Abstract

Web Usage Mining (WUM) is one of the categories of data mining technique that identifies usage patterns of the web data, so as to perceive and better serve the requirements of the web applications. The working of WUM involves three steps - preprocessing, pattern discovery and analysis. The first step in WUM - Preprocessing of data is an essential activity which will help to improve the quality of the data and successively the mining results. This research paper studies and presents several data preparation techniques of access stream even before the mining process can be started and these are used to improve the performance of the data preprocessing to identify the unique sessions and unique users. The methods proposed will help to discover meaningful pattern and relationships from the access stream of the user and these are proved to be valid and useful by various research tests. The paper is concluded by proposing the future research directions in this space.