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Transfer collaborative filtering from multiple sources via consensus regularization

文献类型：期刊论文

作者Chen, Jingwu3,4; Zheng, Jing2; Zhuang, Fuzhen3,4; Zhang, Xiangliang1; Shi, Chuan2; He, Qing3,4
刊名NEURAL NETWORKS
出版日期2018-12-01
卷号108页码:287-295
关键词Collaborative filtering Transfer learning Multiple sources Consensus regularization
ISSN号0893-6080
DOI10.1016/j.neunet.2018.08.022
英文摘要Collaborative filtering is one of the most successful approaches to build recommendation systems. Recently, transfer learning has been applied to recommendation systems for incorporating information from external sources. However, most existing transfer collaborative filtering algorithms tend to transfer knowledge from one single source domain. Rich information is available in many source domains, which can better complement the data in the target domain than that from a single source. However, it is common to get inconsistent information from different sources. To this end, we proposed a TRAnsfer collaborative filtering framework from multiple sources via ConsEnsus Regularization, called TRACER for short. The TRACER framework handles the information inconsistency with a consensus regularization, which enforces the outputs from multiple sources to converge. In addition, our algorithm is to learn and transfer knowledge at the same time while most of the traditional transfer learning algorithms are to learn knowledge first and then transfer it. Experiments conducted on two real-world data sets validate the effectiveness of the proposed algorithm. (C) 2018 Elsevier Ltd. All rights reserved.
资助项目National Key R&D Program of China[2018YFB1004300] ; National Natural Science Foundation of China[61773361] ; National Natural Science Foundation of China[61473273] ; National Natural Science Foundation of China[91546122] ; Science and Technology Project of Guangdong Province[2015B010109005] ; Project of Youth Innovation Promotion Association CAS[2017146]
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000450298900021
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.204/handle/2XEOYT63/4343]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhuang, Fuzhen
作者单位1.King Abdullah Univ Sci & Technol, Thuwal, Saudi Arabia
2.Beijing Univ Posts & Telecommun, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Jingwu,Zheng, Jing,Zhuang, Fuzhen,et al. Transfer collaborative filtering from multiple sources via consensus regularization[J]. NEURAL NETWORKS,2018,108:287-295.
APA Chen, Jingwu,Zheng, Jing,Zhuang, Fuzhen,Zhang, Xiangliang,Shi, Chuan,&He, Qing.(2018).Transfer collaborative filtering from multiple sources via consensus regularization.NEURAL NETWORKS,108,287-295.
MLA Chen, Jingwu,et al."Transfer collaborative filtering from multiple sources via consensus regularization".NEURAL NETWORKS 108(2018):287-295.

入库方式： OAI收割

来源：计算技术研究所

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