Effective Web personalization system using Modified Fuzzy Possibilistic C Means

Due to the rapid growth and development there is an urgent need for the novel technique for the online information system. Web site personalization can be defined as the process of customizing the content and structure of a Web site to the specific and individual needs of each user taking advantage of the user?s navigational behavior. A Web personalization system that dynamically suggests interesting URLs for the current user is a major research area of great interest. Clustering plays a very important role in the development of the web personalization. Fuzzy clustering techniques are found to be very efficient in the clustering accuracy. In this paper, a novel technique is proposed for the development of the web personalization system using the Modified Fuzzy Possibilistic C Means (MFPCM). The performance of the proposed Web Personalization system is evaluated based on various parameters. It is observed from the experimental result that the proposed system with MFPCM is effective in providing better and interesting URLs.