Online Community Identification over Heterogeneous Attributed Directed Graphs
文献类型：会议论文
| 作者 | Wang ZZ(王泽众)2,3,4 ; Zhou, Xiangmin1; Ma, Yuliang3; Yi, Xun1
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| 出版日期 | 2020 |
| 会议日期 | November 12-14, 2020 |
| 会议地点 | Foshan, China |
| 关键词 | Online community identification User identity linkage Attributed directed graphs |
| 页码 | 266-280 |
| 英文摘要 | The creating of communities has resulted in the astonishing increase in many areas. Especially in the area of social networks, it has wide applications in the domains such as product recommendation, setting up social events, online games etc. The applications are relied on effective solutions for retrieving communities online. In this way, a great deal of research has been conducted on yielding communities. Unfortunately, the state-of-the-art community identity methods which aim to find out communities containing the query nodes, only consider topological structure, but ignore the effect of nodes’ attribute, direction between nodes, and nodes’ information across heterogeneous graphs, lead to communities with poor cohesion. Thus, we address the problem of discovering communities online, across heterogeneous directed attributed graphs. We first propose an online method to match pairs of users in heterogeneous graphs and combine them into a new one. Then we propose IC-ADH, a novel framework of retrieving communities in the new directed attributed graph. Extensive experiments demonstrate the effectiveness of our proposed solution across heterogeneous directed attributed graphs. |
| 产权排序 | 1 |
| 会议录 | Advanced Data Mining and Applications - 16th International Conference, ADMA 2020, Proceedings
 |
| 会议录出版者 | Springer Science and Business Media Deutschland GmbH |
| 会议录出版地 | Berlin |
| 语种 | 英语 |
| ISSN号 | 0302-9743 |
| ISBN号 | 978-3-030-65389-7 |
| WOS记录号 | WOS:000723588900021 |
| 源URL | [http://ir.sia.cn/handle/173321/28364]  |
| 专题 | 沈阳自动化研究所_水下机器人研究室 |
| 通讯作者 | Wang ZZ(王泽众) |
| 作者单位 | 1.School of Science, RMIT University, Melbourne, VIC 3000, Australia 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.School of Computer Science and Engineering, Northeastern University, Shenyang, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
| 推荐引用方式 GB/T 7714 | Wang ZZ,Zhou, Xiangmin,Ma, Yuliang,et al. Online Community Identification over Heterogeneous Attributed Directed Graphs[C]. 见:. Foshan, China. November 12-14, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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