Exploiting higher-order patterns for community detection in attributed graphs | |
Hu, L (Hu, Lun)[ 1 ]; Pan, XY (Pan, Xiangyu)[ 2 ]; Yan, H (Yan, Hong)[ 3 ]; Hu, PW (Hu, Pengwei)[ 4 ]; He, TT (He, Tiantian)[ 5 ] | |
刊名 | INTEGRATED COMPUTER-AIDED ENGINEERING |
2021 | |
卷号 | 28期号:2页码:207-218 |
关键词 | Attributed graph community detection clustering higher-order patterns |
ISSN号 | 1069-2509 |
DOI | 10.3233/ICA-200645 |
英文摘要 | As a fundamental task in cluster analysis, community detection is crucial for the understanding of complex network systems in many disciplines such as biology and sociology. Recently, due to the increase in the richness and variety of attribute information associated with individual nodes, detecting communities in attributed graphs becomes a more challenging problem. Most existing works focus on the similarity between pairwise nodes in terms of both structural and attribute information while ignoring the higher-order patterns involving more than two nodes. In this paper, we explore the possibility of making use of higher-order information in attributed graphs to detect communities. To do so, we first compose tensors to specifically model the higher-order patterns of interest from the aspects of network structures and node attributes, and then propose a novel algorithm to capture these patterns for community detection. Extensive experiments on several real-world datasets with varying sizes and different characteristics of attribute information demonstrated the promising performance of our algorithm. |
WOS记录号 | WOS:000626773100007 |
内容类型 | 期刊论文 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7824] |
专题 | 新疆理化技术研究所_多语种信息技术研究室 |
作者单位 | 1.Nanyang Technol Univ, Data Sci & Artificial Intelligence Res Ctr, Sch Comp Sci & Engn, Singapore, Singapore 2.Kriston AI Lab, Xiamen, Fujian, Peoples R China 3.City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China 4.Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China 5.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi, Xinjiang, Peoples R China |
推荐引用方式 GB/T 7714 | Hu, L ,Pan, XY ,Yan, H ,et al. Exploiting higher-order patterns for community detection in attributed graphs[J]. INTEGRATED COMPUTER-AIDED ENGINEERING,2021,28(2):207-218. |
APA | Hu, L ,Pan, XY ,Yan, H ,Hu, PW ,&He, TT .(2021).Exploiting higher-order patterns for community detection in attributed graphs.INTEGRATED COMPUTER-AIDED ENGINEERING,28(2),207-218. |
MLA | Hu, L ,et al."Exploiting higher-order patterns for community detection in attributed graphs".INTEGRATED COMPUTER-AIDED ENGINEERING 28.2(2021):207-218. |
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