GiveALink is a public site where users donate their bookmarks to the Web community. Bookmarks are analyzed to build a new generation of Web mining techniques and new ways to search, recommend, surf, personalize and visualize the Web. We present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure of the bookmark files of individual users, and of collaborative filtering across users. We analyze the social bookmark network induced by the similarity measure. A search and recommendation system is built from a number of ranking algorithms based on prestige, generality, and novelty measures extracted from the similarity data.
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