An adaptive method for the tag-rating-based recommender system
AMT'12 Proceedings of the 8th international conference on Active Media Technology
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Social bookmarking is emerging as a new information infrastructure on the web, and has the ability of organizing multicultural metadata for large scale of digital entities. To achieve its potential, we propose a technique to extract the substantial correlation among tags. Based on it, we maintain profiles for users' interests, and recommend items according to them. Experiments against data from del.icio.us reveal the superiority of our method.