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http://dx.doi.org/10.13089/JKIISC.2018.28.1.241

Design and Analysis a Robust Recommender System Exploiting the Effect of Social Trust Clusters  

Noh, Giseop (Cheongju University)
Oh, Hayoung (Ajou University)
Lee, Jaehoon (Seoul National University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.28, no.1, 2018 , pp. 241-248 More about this Journal
Abstract
A Recommender System (RS) is a system that provides optimized information to users in an over-supply situation. The key to RS is to accurately predict the behavior of the user. The Matrix Factorization (MF) method was used for this prediction in the early stage, and according to the recent SNS development, social information is additionally utilized to improve prediction accuracy. In this paper, we use RS internal trust cluster, which was overlooked in previous studies, to further improve performance and analyze the characteristics of trust clusters.
Keywords
Trust Cluster; Social Relation; Robust Recommender System; Prediction Accuracy;
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