Computer Science – Social and Information Networks
Scientific paper
2012-03-01
Original language English, Journal CEUR Workshop Proceedings, Publication date 2009, Volume 485, Pages 40-49, ISSN 1613-0073
Computer Science
Social and Information Networks
Scientific paper
Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. In this paper, we present a tag-based recommender system which suggests similar Web pages based on the similarity of their tags from a Web 2.0 tagging application. The proposed approach extends the basic similarity calculus with external factors such as tag popularity, tag representativeness and the affinity between user and tag. In order to study and evaluate the recommender system, we have conducted an experiment involving 38 people from 12 countries using data from Del.icio.us, a social bookmarking web system on which users can share their personal bookmarks.
Dolog Peter
Durao Frederico
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