Improving the performance of web search using users' bookmarks

In this paper we propose using the bookmark and combination with the other feature for web search engine. As the majority of current web search engines use keyword-based method for similarity computing, they cannot discriminate important web pages among huge amount of search results. The proposed system reflects collaborative evaluation by users by accumulating the number of bookmark on a web page. In this paper we implement a user interface that helps to store bookmark count and click count separately according to pages by multiple users, and estimate a ranking function though several features on returned result page. The experimental results show that the accuracy of proposed system is improved by as much as 30.5% compared to conventional web search engines.