期刊
ICT EXPRESS
卷 5, 期 2, 页码 84-88出版社
ELSEVIER
DOI: 10.1016/j.icte.2018.05.003
关键词
Collaborative Filtering; Neural Network
资金
- Basic Science Research Program through NRF - MSIP [NRF-2017R1A2B2007102]
- Technology Innovation Program - MOTIE [10051928]
- Bio-Mimetic Robot Research Center - DAPA [UD130070ID]
- INMAC
- BK21-plus
We propose a novel collaborative filtering algorithm based on deep neural networks. We use normalized user-rating vector and normalized item-rating vector as inputs to a neural network. The batch normalization technique is used for each layer to prevent neural networks from overfitting. Experimental results show that the proposed method outperforms conventional collaborative filtering algorithms. Based on the results, its performance is comparable to the well-known Netflix prize winning algorithm by BellKor. The proposed method has another strong advantage that online operation is possible with little extra complexity and performance degradation. (C) 2018 The Korean Institute of Communications and Information Sciences (KICS). Publishing Services by Elsevier B.V.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据