Cross-OSN User Modeling by Homogeneous Behavior Quantification and Local Social Regularization
文献类型:期刊论文
作者 | Sang, Jitao1![]() ![]() |
刊名 | IEEE TRANSACTIONS ON MULTIMEDIA
![]() |
出版日期 | 2015-12-01 |
卷号 | 17期号:12页码:2259-2270 |
关键词 | Behavior fusion cross-OSN user modeling local social regularization personalization video recommendation |
英文摘要 | 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. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications |
研究领域[WOS] | Computer Science ; Telecommunications |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000365315500013 |
公开日期 | 2016-02-26 |
源URL | [http://ir.ia.ac.cn/handle/173211/10520] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
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 |
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. |
入库方式: OAI收割
来源:自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。