Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization

doi:10.1109/TMM.2015.2486524

	Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization
	Sang, Jitao1 ; Deng, Zhengyu 1; Lu, Dongyuan 2; Xu, Changsheng1
发表期刊	IEEE TRANSACTIONS ON MULTIMEDIA
	2015-12-01
卷号	17 期号:12 页码:2259-2270
文章类型	Article
摘要	In the context of social media services, data shortage has severally hindered accurate user modeling and practical personalized applications. This paper is motivated to leverage the user data distributed in disparate online social networks (OSN) to make up for the data shortage in user modeling, which we refer to as "cross-OSN user modeling." Generally, the data that the same user distributes in different OSNs consist of both behavior data (i.e., interaction with multimedia items) and social data (i.e., interaction between users). This paper focuses on the following two challenges: 1) how to aggregate the users' cross-OSN interactions with multimedia items of the same modality, which we call cross-OSN homogeneous behaviors, and 2) how to integrate users' cross-OSN social data with behavior data. Our proposed solution to address the challenges consist of two corresponding components as follows. 1) Homogeneous behavior quantification, where homogeneous user behaviors are quantified based on their importance in reflecting user preferences. After quantification, the examined cross-OSN user behaviors are aggregated to construct a unified user-item interaction matrix. 2) Local social regularization, where the cross-OSN social data is integrated as regularization in matrix factorization-based user modeling at local topic level. The proposed cross-OSN user modeling solution is evaluated in the application of personalized video recommendation. Carefully designed experiments on self-collected Google+ and YouTube datasets have validated its effectiveness and the advantage over single-OSN-based methods.
关键词	Behavior Fusion Cross-osn User Modeling Local Social Regularization Personalization Video Recommendation
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TMM.2015.2486524
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(61225009 ; Beijing Natural Science Foundation(4131004) ; 61332016 ; 61303176)
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号	WOS:000365315500013
引用统计	被引频次：16[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/173211/10520
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, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.Univ Int Business & Econ, Sch Informat Technol & Management, Beijing 100029, Peoples R China
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	Sang, Jitao,Deng, Zhengyu,Lu, Dongyuan,et al. Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2015,17(12):2259-2270.
APA	Sang, Jitao,Deng, Zhengyu,Lu, Dongyuan,&Xu, Changsheng.(2015).Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization.IEEE TRANSACTIONS ON MULTIMEDIA,17(12),2259-2270.
MLA	Sang, Jitao,et al."Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization".IEEE TRANSACTIONS ON MULTIMEDIA 17.12(2015):2259-2270.

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文件名称/大小	文献类型	版本类型	开放类型	使用许可
Cross-OSN User Model（2027KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览