There is an increasing demand for finding related Web pages when we encounter a Web page that makes us feel like knowing more about the page. However, with general-purpose search engines, users have to predict query terms and phrases that may be included in the target Web pages. Since this is a formidable task for users, a new-style search method is strongly expected, which makes it possible to retrieve related Web pages from a seed Web page. We will focus on Social Bookmark (SBM) services, and propose a method for finding related pages by taking advantage of collective information from SBM members and their tags. Our proposed method relies on the observation that there is a tendency that the same users put the same tags to similar Web pages. We will address our implemented system for retrieving related Web pages by utilizing the above observation, and report the evaluation results.
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