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This problem can be using two-way hash table structure as Access History List. In our system, session identification is done using AHL by considering immediate link analysis, backward referencing without searching the whole tree representing the server pages. Based on this study, it can be concluded that the system is complex but user session sequences are generated with less time and greater precision. | International Journal of Computer Networks and Communications Security C VOL.1, NO.7, DECEMBER 2013, 284–291 Available online at: www.ijcncs.org ISSN 2308-9830 N C S Improved Data Preparation Technique in Web Usage Mining Mona S. Kamat1, Dr. J.W.Bakal2, Madhu Nashipudi3 1, 3 Information Technology Department, Pillai Institute of Information Technology (PIIT), Panvel, Navi Mumbai, India 2 Shivajirao S. Jondhale College Of Engineering (SSJCOE), Dombivali, Thane, India E-mail: 1monakamat@gmail.com ABSTRACT The process to discover and extract useful information is web usage mining. It helps to better understand and achieve the needs of web-based applications. To enhance the efficiency and to ease of the mining process, the data should be preprocessed. The proper study and analysis of web log file is useful to manage the websites effectively for administrative and user’s perspective. Many a time the backward referencing used to track the reachability of the pages which consumes time and generates complete path from the root node even if the link has come from some other server page. This problem can be using two-way hash table structure as Access History List. In our system, session identification is done using AHL by considering immediate link analysis, backward referencing without searching the whole tree representing the server pages. Based on this study, it can be concluded that the system is complex but user session sequences are generated with less time and greater precision. Keywords: Session identification, Web usage mining, Preprocessing, Backward reachability. 1 INTRODUCTION Web Usage Mining is the type of Web Mining activity that involves the automatic discovery of user access patterns from various web log access records. This process consists of three main steps: 1. Preprocessing, 2. Pattern Discovery, 3. Pattern Analysis as shown in Fig 1. Organizations often generate and collect large volumes of data coming from various sources in different .
