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http://dx.doi.org/10.5391/JKIIS.2006.16.2.156

A Prediction System of User Preferences for Newly Released Items Based on Words  

Choi, Yoon-Seok (서울대학교 컴퓨터공학부)
Moon, Byung-Ro (서울대학교 컴퓨터공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.2, 2006 , pp. 156-163 More about this Journal
Abstract
CF systems are widely used in recommendation due to the easy implementation and the outstanding performance. They have several problems such as the sparsity problem, the first-rater problem, and recommending explanation. Many studies are suggested to resolve these problems. While the influence of the sparsity problem lessens as the users' data are accumulated, but the first-rater problem is originated from the CF systems and there are a number of researches to overcome the disadvantages of CF systems based on the content-based methods. Also CF systems are black boxes, providing no explanation of working of the recommendation. In this paper we present a content-based prediction system based on the preference words, which exposes the reasoning behind a recommendation. Our system predicts user's rating of a new movie and we suggest a semiotic network-based method to solve the mismatching problem between the items. For experimental comparison, we used EachMovie and IMDb dataset.
Keywords
추천 시스템;선호도 예측;신상품 추천문제;추천 설명;속성 비매칭 문제;
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