Architecture of personalized web search engine using suffix tree clustering

Web search engines are designed to serve all users, independent of the special needs of any individual user. The objective of the project is to develop a personalized web search engine which considers users interest and generates search results based on the user's semantic profile. The proposed system utilizes clustering and re-ranking algorithms in order to organize the web documents and provide an order to the results displayed to the user. Web crawlers are utilized to get the links, images and allied information from the World Wide Web. The fetched documents are further clustered using suffix tree clustering algorithm, which enhances the performance of the web search engine. The results are organized using Page Re-Rank algorithm which considers hyperlink and link structure information to bring an order to the web. The system creates a semantic profile of the user by monitoring and analyzing the users search history. The search results generated will utilize an amalgamation of varied techniques including clustering, re-ranking and semantic user profiles to enhance the performance of the web search engine.