Web Search Result Personalization using Web Mining

The information on the web is growing dramatically. The users have to spend lots of time on the web finding the information they are interested in. Today, he traditional search engines do not give users enough personalized help but provide the user with lots of irrelevant information. In this paper, we present a personalize Web search system, which can helps users to get the relevant web pages based on their selection from the domain list. Thus, users can obtain a set of interested domains and the web pages from the system. The system is based on features extracted from hyperlinks, such as anchor terms or URL tokens, user interest domains and past search results. Our methodology uses an innovative weighted URL Rank algorithm based on user interested domains and user query.