User community discovery from multi-relational networks

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	User community discovery from multi-relational networks
	Zhang, Zhongfeng 1; Li, Qiudan1 ; Zeng, Daniel1,2 ; Gao, Heng 1
发表期刊	DECISION SUPPORT SYSTEMS
	2013
卷号	54 期号:2 页码:870-879
文章类型	Article
摘要	Online social network services (SNS) have been experiencing rapid growth in recent years. SNS enable users to identify other users with common interests, exchange their opinions, and establish forums for communication, and so on. Discovering densely connected user communities from social networks has become one of the major challenges, to help understand the structural properties of SNS and improve user-oriented services such as identification of influential users and automated recommendations. Previous work on community discovery has treated user friendship networks and user-generated contents separately. We hypothesize that these two types of information can be fruitfully integrated and propose a unified framework for user community discovery in online social networks. This framework combines the author-topic (AT) model with user friendship network analysis. We empirically show that this approach is capable of discovering interesting user communities using two real-world datasets. (C) 2012 Elsevier B.V. All rights reserved.
关键词	Community Discovery Multi-relational Network Author Topic Model Non-negative Matrix Factorization
WOS标题词	Science & Technology ; Technology
关键词[WOS]	NONNEGATIVE MATRIX FACTORIZATION ; SOCIAL NETWORK ; ONLINE COMMUNITIES ; KNOWLEDGE ; SYSTEMS
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Operations Research & Management Science
WOS记录号	WOS:000317448900007
引用统计	被引频次：37[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/173211/2928
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Li, Qiudan
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhang, Zhongfeng,Li, Qiudan,Zeng, Daniel,et al. User community discovery from multi-relational networks[J]. DECISION SUPPORT SYSTEMS,2013,54(2):870-879.
APA	Zhang, Zhongfeng,Li, Qiudan,Zeng, Daniel,&Gao, Heng.(2013).User community discovery from multi-relational networks.DECISION SUPPORT SYSTEMS,54(2),870-879.
MLA	Zhang, Zhongfeng,et al."User community discovery from multi-relational networks".DECISION SUPPORT SYSTEMS 54.2(2013):870-879.

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