HE Ming, REN Wanpeng. Attribute Reduction with Rough Set in Context-Aware Collaborative Filtering[J]. Chinese Journal of Electronics, 2017, 26(5): 973-980. doi: 10.1049/cje.2016.10.022
Citation: HE Ming, REN Wanpeng. Attribute Reduction with Rough Set in Context-Aware Collaborative Filtering[J]. Chinese Journal of Electronics, 2017, 26(5): 973-980. doi: 10.1049/cje.2016.10.022

Attribute Reduction with Rough Set in Context-Aware Collaborative Filtering

doi: 10.1049/cje.2016.10.022
Funds:  This work is supported by Natural Science Foundation of Beijing (No.4153058).
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  • Corresponding author: HE Ming (corresponding author) was born in 1975. He received Ph.D. degree from Xi'an Jiaotong University in 2005. He is now a associate professor and Master's supervisor in Beijing University of Techology. His research interests include recommendation systems, data mining and machine learning. (Email:heming@bjut.edu.cn)
  • Received Date: 2015-12-22
  • Rev Recd Date: 2016-03-04
  • Publish Date: 2017-09-10
  • The problem of different contextual information to influence the user-item-context interactions at varying degrees in context-aware recommender systems is addressed. To improve the performance accuracy, we develop a novel attribute reduction algorithm in order to effectively extract the core contextual information using rough set. We combine collaborative filtering with contextual information significance to generate more accurate predictions. We experimentally evaluate our approach on UCI machine learning repository and two real world data sets. Experimental results demonstrate that our proposed approach outperforms existing state-of-theart context-aware recommendation methods.
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