ADAPTIVE WEB BROWSER

Abstract

Web browser play important role in World Wide Web (WWW). We go through different website and invest enough time searching relevant URL. The project deals with making a browser that will assist a person to find relevant information satisfying long term recurring goals rather than short term goals and describe our research on learning browser behaviour model for predicting the current information need of web user. Depending upon the user sequence of browsing behaviour it indicates the degree to which page content satisfies user’s need. Thus one’s search experience may be used to help the next users to reduce their searching effort. So, through more and more searching greater experience will be gained by browser. We deploy extensive use of machine learning for the browser to learn user’s behaviour.  By such model the searching ability of browser becomes more efficient and faster thus resulting in an intelligent and adaptive web browser.