Collective intelligence-based web page search: Combining folksonomy and link-based ranking strategy

Abstract

With the exponentially growing amount of information available on the Internet, retrieving web pages of interest has become increasingly difficult. While several web page recommender systems have been developed, it is still difficult to search related information which reflects users' preference. In this paper, we propose a new type of web page search which is based on the collective intelligence. It combines folksonomy and link-based ranking evaluation scheme so as to accommodate users' preferences. We implemented the prototype system and demonstrate the feasibility of the proposed web page search scheme.