Sunday 28th of April 2024
 

Efficient Web Usage Mining With Clustering


K. Poongothai, M. Parimala and S. Sathiyabama

Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis etc., Web site under study is part of a nonprofit organization that does not sell any products. It was crucial to understand who the users were, what they looked at, and how their interests changed with time. To achieve this, one of the promising approaches is web usage mining, which mines web logs for user models and recommendations. Web usage mining algorithms have been widely utilized for modeling user web navigation behavior. In this study we advance a model for mining of user\'s navigation pattern. The proposal of our work proceeds in the direction of building a robust web usage knowledge discovery system, which extracts the web user profiles at the web server, application server and core application level. The proposal optimizes the usage mining framework with fuzzy C means clustering algorithm (to discover web data clusters) and compare with Expected Maximization cluster system to analyze the Web site visitor trends. The evolutionary clustering algorithm is proposed to optimally segregate similar user interests. The clustered data is then used to analyze the trends using inference system. By linking the Web logs with cookies and forms, it is further possible to analyze the visitor behavior and profiles which could help an e-commerce site to address several business questions. Experimentation conducted with CFuzzy means and Expected Maximization clusters in Syskill Webert data set from UCI, shows that EM shows 5% to 8% better performance than CFuzzy means in terms of cluster number.

Keywords: web usage mining

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ABOUT THE AUTHORS

K. Poongothai
K.Poongothai received the M.Sc (IT). Degree in Information Technology from M.Kumarasamy College of Engineering,Karur in 2006 respectively. Presently she is working in Selvam College of Technology, Namakkal, and Tamilnadu, India as Assistant Professor in Department of Information Technology.

M. Parimala
M.Parimala received the MCA. Degree in Computer Application from Mother Theresa Women\'s University, Kodaikanal in 2005 respectively. Presently she is working in M.Kumarasamy College of Engineering,Karur Tamilnadu, India as Lecturer in Department of Computer Application.

S. Sathiyabama
Dr.S.Sathyabama received the M.Sc.in Avinashilingam Deemed University, Coimbatore in 1997, M.Phil in Bharathiar University, Coimbatore in 2001 and Ph.D. degree in Periyar University in 2007, Salem. She worked as Lecturer from 1997 to 2001 in karuppannan Mariappan College, Muthur. , she worked as a Professor in the Department of Master of Computer Application from 2001 to 2011 at K.S.Rangasamy College of Technology and presently she is working as Assistant Professor of Computer Science, Thiruvalluvar Govt Arts and science college, Rasipuram.


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