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http://dx.doi.org/10.6109/jkiice.2013.17.11.2602

A Movie Recommendation Method Using Rating Difference Between Items  

Oh, Se-Chang (Department of Information & Communication, Sejong Cyber University)
Choi, Min (Department of Information and Communication Engineering, Chungbuk National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.11, 2013 , pp. 2602-2608 More about this Journal
Abstract
User-based and item-based method have been developed as the solutions of the movie recommendation problem. However, these methods are faced with the sparsity problem and the problem of not reflecting user's rating respectively. In order to solve these problems, there is a research on the combination of the two methods using the concept of similarity. In reality, it is not free from the problem of sparsity, since it has a lot of parameters to be calculated. In this study, we propose a recommendation method using rating difference between items in order to complement this problem. This method is relatively free from the problem of sparsity, since it has less parameters to be calculated. And it can get more accurate results by reflecting the users rating to calculate the parameters. In experiments for the proposed method, the initial error is large, but the performance has been quickly stabilized after. In addition, it showed a 0.0538 lower average error compared to the existing method using similarity.
Keywords
Collaborative Filtering; Recommender System; Data Mining; Sparsity; Electronic Commerce;
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Times Cited By KSCI : 1  (Citation Analysis)
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