Web usage prediction has become a widely addressed topic with the huge proliferation of World Wide Web and computers. Most of the work done in this area of research is centered around prediction of what links the user is expected to visit next given his usage history, making suggestions for new web-sites he may be interested in and the like. We propose two algorithms to make browsers intelligent enough to gauge usage patterns.
This algorithms are a blend of statistical and fuzzy logic techniques to gauge the surfing pattern of users, hence intelligently predicting the time ranges of likely user hits for particular websites, speeding up the browsing experience by means of caching and preloading of predicted websites.
Thus our design intends to make the browsers intelligent to speed up and better organize the browsing experience.