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Evaluating collaborative filtering recommender systems
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WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
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AMT '09 Proceedings of the 5th International Conference on Active Media Technology
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AI Communications
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In this paper we study the challenges and evaluate the effectiveness of data collected from the web for recommendations. We provide experimental results, including a user study, showing that our methods produce good recommendations in realistic applications. We propose a new evaluation metric, that takes into account the difficulty of prediction. We show that the new metric aligns well with the results from a user study.