CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
A Unified Video Recommendation by Cross-Network User Modeling
Yan, Ming1,2; Sang, Jitao1,3; Xu, Changsheng1,2; Hossain, M. Shamim4
Source PublicationACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
2016-08-01
Volume12Issue:4Pages:1-24
SubtypeArticle
AbstractOnline 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.
KeywordAlgorithms Experimentation Performance Personalized Video Recommendation Cross-network Collaboration User Modeling
WOS HeadingsScience & Technology ; Technology
DOI10.1145/2957755
Indexed BySCI
Language英语
Funding OrganizationNational 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 Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS IDWOS:000382877500007
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12630
Collection模式识别国家重点实验室_多媒体计算与图形学
Affiliation1.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
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
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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