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Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization
Sang, Jitao1; Deng, Zhengyu1; Lu, Dongyuan2; Xu, Changsheng1
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
2015-12-01
Volume17Issue:12Pages:2259-2270
SubtypeArticle
AbstractIn 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.
KeywordBehavior Fusion Cross-osn User Modeling Local Social Regularization Personalization Video Recommendation
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TMM.2015.2486524
Indexed BySCI
Language英语
Funding OrganizationNational Basic Research Program of China(2012CB316304) ; National Natural Science Foundation of China(61225009 ; Beijing Natural Science Foundation(4131004) ; 61332016 ; 61303176)
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000365315500013
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10520
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, 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
Recommended Citation
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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