Institute of Computing Technology, Chinese Academy IR
Transfer collaborative filtering from multiple sources via consensus regularization | |
Zhuang, Fuzhen1,2; Zheng, Jing3; Chen, Jingwu1,2; Zhang, Xiangliang4; Shi, Chuan3; He, Qing1,2 | |
2018-12-01 | |
发表期刊 | NEURAL NETWORKS |
ISSN | 0893-6080 |
卷号 | 108页码:287-295 |
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. |
关键词 | Collaborative filtering Transfer learning Multiple sources Consensus regularization |
DOI | 10.1016/j.neunet.2018.08.022 |
收录类别 | SCI |
语种 | 英语 |
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 |
WOS类目 | Computer Science, Artificial Intelligence ; Neurosciences |
WOS记录号 | WOS:000450298900021 |
出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/4344 |
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.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Beijing Univ Posts & Telecommun, Beijing, Peoples R China 4.King Abdullah Univ Sci & Technol, Thuwal, Saudi Arabia |
推荐引用方式 GB/T 7714 | Zhuang, Fuzhen,Zheng, Jing,Chen, Jingwu,et al. Transfer collaborative filtering from multiple sources via consensus regularization[J]. NEURAL NETWORKS,2018,108:287-295. |
APA | Zhuang, Fuzhen,Zheng, Jing,Chen, Jingwu,Zhang, Xiangliang,Shi, Chuan,&He, Qing.(2018).Transfer collaborative filtering from multiple sources via consensus regularization.NEURAL NETWORKS,108,287-295. |
MLA | Zhuang, Fuzhen,et al."Transfer collaborative filtering from multiple sources via consensus regularization".NEURAL NETWORKS 108(2018):287-295. |
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