A Process Oriented Perception of Personalization Techniques in Web Mining
Gopal Pandey1, SwatiPatel2, Vidhu Singhal3, Akshay Kansara4
1Prof. Gopal Pandey, Department of Information Technology, Sir Bhavsinhji Polytechnic Institute, Bhavnagar, Gujarat, India
2Prof. Swati Patel , Department of Computer Science, L.D.College of Engineering, Ahmedabad, Gujarat, India
3Vidhu Singhal, Department of Information Technology, Shantilal Shah Engineering College, Bhavnagar, Gujarat, India
4Akshay Kansara, Department of Information Technology, L.D.College of Engineering, Ahmedabad, Gujarat, India.
Manuscript received January 06, 2013. | Revised Manuscript received on January 12, 2013. | Manuscript published on January 15, 2013. | PP: 26-30 | Volume-1, Issue-2, January 2013. | Retrieval Number: B0127011213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Web personalization is an approach, a marketing tool and a fine art. With the rapid development of Deep Web, a large number of web information often lead to “information overload” and “information disorientated “, yet, personalized techniques can solve this problem. Personalized techniques are one such software tool used to help users obtain recommendations for unseen items based on their preferences. The commonly used personalized techniques are content based filtering, collaborative filtering and rule based filtering. In this paper, we present a survey on a personalized collaborative filtering method combining the association rule mining focusing on the problems that have been identifying and the solution that have been proposed.
Keywords: Association rule mining, collaborative filtering, personalization, web mining, web usage mining