Dynamic Web Site Adaptation by Applying Web usage Mining Techniques

In the Cyberspace, most people are tailored to obtain intelligence from the World Wide Web. To endure and flourish, a Web site has to constantly encourage its overall layout and potentials while providing a variety of constructive information services to attract users. The Web Recommendation System prompts users to visit a Web site and browse at a deeper level. Using large browsing patterns don't satisfy user's dynamic need. The requirement for an adaptive recommendation system comes into the modern world to encourage the online users to get required details immediately. This paper proposes a novel Web recommendation framework, based on Page Classification Algorithm which can respond to new navigation trends and dynamically adapts recommendations for users with suitable suggestions through hyperlinks. This research enables Web sites with dynamic intelligence to effectively tailor users' needs by means of personalization. User behavior is identified for the improvement of website design