Community detection in attributed networks using neighborhood information

doi:10.1007/s10586-024-04457-9

LZUFE-KMS

	Community detection in attributed networks using neighborhood information
	Wang, Xiaozong 1; Tang, Fengqin 1; Wang, Yuanyuan 2; Li, Cuixia 3; Zhao, Xuejing 4
	2024-04-10
在线发表日期	2024-04
发表期刊	CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
卷号	27 期号:6 页码:8349-8366
摘要	Community detection is a crucial aspect in network analysis. Real-world networks are often enriched with attributes providing extensive information for nodes beyond mere topology. Integrating these nodal attributes into community detection for attributed networks poses notable challenges and remains an active research field. In this paper, we propose a novel method that incorporates structural information into fused attributes. This is achieved by defining a fusion similarity between nodes, which is a convex combination of topology similarity, pairwise attribute similarity, and attribute similarity with their immediate neighbors. One advantage of the proposed method is its flexibility in identifying communities in disassortative networks, where nodes exhibit more connections between different groups than within their own group. We employ an iterative spectral clustering technique to discover communities and assess the influence of various attributes within these communities. Our experimental results validate the effectiveness of this approach, demonstrating its utility in leveraging node attributes in diverse simulated and real-world network datasets.
关键词	Community detection Disassortative stochastic block model Spectral clustering Fusion attribute similarity
DOI	10.1007/s10586-024-04457-9
收录类别	SCIE ; EI
ISSN	1386-7857
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS记录号	WOS:001200416000003
出版者	SPRINGER
EI入藏号	20241515903218
EI主题词	Topology
EI分类号	723.2 Data Processing and Image Processing ; 731.1 Control Systems ; 903.1 Information Sources and Analysis ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory ; 921.6 Numerical Methods ; 922.1 Probability Theory ; 961 Systems Science ; 971 Social Sciences
原始文献类型	Article ; Early Access
EISSN	1573-7543
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/36168
专题	兰州财经大学
通讯作者	Tang, Fengqin
作者单位	1.Huaibei Normal Univ, Sch Math & Stat, Huaibei, Peoples R China; 2.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou, Peoples R China; 3.Xuzhou Univ Technol, Sch Math & Stat, Xuzhou, Peoples R China; 4.Lanzhou Univ, Sch Math & Stat, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Wang, Xiaozong,Tang, Fengqin,Wang, Yuanyuan,et al. Community detection in attributed networks using neighborhood information[J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS,2024,27(6):8349-8366.
APA	Wang, Xiaozong,Tang, Fengqin,Wang, Yuanyuan,Li, Cuixia,&Zhao, Xuejing.(2024).Community detection in attributed networks using neighborhood information.CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS,27(6),8349-8366.
MLA	Wang, Xiaozong,et al."Community detection in attributed networks using neighborhood information".CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 27.6(2024):8349-8366.