A Unified Video Recommendation by Cross-Network User Modeling

doi:10.1145/2957755

	A Unified Video Recommendation by Cross-Network User Modeling
	Yan, Ming1,2 ; Sang, Jitao1,3 ; Xu, Changsheng1,2 ; Hossain, M. Shamim 4
发表期刊	ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
	2016-08-01
卷号	12 期号:4 页码:1-24
文章类型	Article
摘要	Online video sharing sites are increasingly encouraging their users to connect to the social network venues such as Facebook and Twitter, with goals to boost user interaction and better disseminate the high-quality video content. This in turn provides huge possibilities to conduct cross-network collaboration for personalized video recommendation. However, very few efforts have been devoted to leveraging users' social media profiles in the auxiliary network to capture and personalize their video preferences, so as to recommend videos of interest. In this article, we propose a unified YouTube video recommendation solution by transferring and integrating users' rich social and content information in Twitter network. While general recommender systems often suffer from typical problems like cold-start and data sparsity, our proposed recommendation solution is able to effectively learn from users' abundant auxiliary information on Twitter for enhanced user modeling and well address the typical problems in a unified framework. In this framework, two stages are mainly involved: (1) auxiliary-network data transfer, where user preferences are transferred from an auxiliary network by learning cross-network knowledge associations; and (2) cross-network data integration, where transferred user preferences are integrated with the observed behaviors on a target network in an adaptive fashion. Experimental results show that the proposed cross-network collaborative solution achieves superior performance not only in terms of accuracy, but also in improving the diversity and novelty of the recommended videos.
关键词	Algorithms Experimentation Performance Personalized Video Recommendation Cross-network Collaboration User Modeling
WOS标题词	Science & Technology ; Technology
DOI	10.1145/2957755
收录类别	SCI
语种	英语
项目资助者	National Basic Research Program of China(2012CB316304) ; National Natural Science Foundation of China(61432019 ; Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia(RGP-228) ; 61225009 ; 61303176 ; 61272256 ; 61373122 ; 61332016)
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS记录号	WOS:000382877500007
引用统计	被引频次：23[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12630
专题	多模态人工智能系统全国重点实验室_多媒体计算
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Nanjing Univ, State Key Lab Novel Software Technol, Nanjing, Jiangsu, Peoples R China 4.King Saud Univ, Coll Comp & Informat Sci, Dept Software Engn, Riyadh 11543, Saudi Arabia
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Yan, Ming,Sang, Jitao,Xu, Changsheng,et al. A Unified Video Recommendation by Cross-Network User Modeling[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2016,12(4):1-24.
APA	Yan, Ming,Sang, Jitao,Xu, Changsheng,&Hossain, M. Shamim.(2016).A Unified Video Recommendation by Cross-Network User Modeling.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,12(4),1-24.
MLA	Yan, Ming,et al."A Unified Video Recommendation by Cross-Network User Modeling".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 12.4(2016):1-24.

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