User community discovery from multi-relational networks
文献类型：期刊论文
| 作者 | Zhang, Zhongfeng1; Li, Qiudan1 ; Zeng, Daniel1,2; Gao, Heng1
|
| 刊名 | DECISION SUPPORT SYSTEMS
 |
| 出版日期 | 2013 |
| 卷号 | 54期号:2页码:870-879 |
| 关键词 | Community discovery Multi-relational network Author topic model Non-negative matrix factorization |
| 通讯作者 | Li, Qiudan |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Operations Research & Management Science |
| 研究领域[WOS] | Computer Science ; Operations Research & Management Science |
| 关键词[WOS] | NONNEGATIVE MATRIX FACTORIZATION ; SOCIAL NETWORK ; ONLINE COMMUNITIES ; KNOWLEDGE ; SYSTEMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000317448900007 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/2928]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
| 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 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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