A novel recommender system fusing the opinions from experts and ordinary people

Authors:
Pei Wu;Weiping Liu;Cihang Jin
Affiliations:
University of Fribourg, Fribourg, Switzerland;University of Fribourg, Fribourg, Switzerland;University of Fribourg, Fribourg, Switzerland
Venue:
Proceedings of the Workshop on Context-Aware Movie Recommendation
Year:
2010

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Abstract

In this paper, we propose a novel recommendation algorithm fusing the opinions from experts and ordinary people. Instead of regarding one's judgement capability as his/her expertise, we present a new definition which measures the amount of the recommendable items one know in a certain area. When computing the expertise, we consider both the average value and the accumulative value, and introduce a free parameter α to tune between these two values. To evaluate the proposed algorithm, simulations are run on the Moviepilot dataset, and the results demonstrate that our algorithm outperforms the conventional collaborative filtering algorithm.