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Alleviating the resolution limit problem in spatial community detection: a local network structure-based method

文献类型：期刊论文

作者Liu, Wenkai1,2,3; Cai, Haonan3; Xing, Hanfa2,3; Hu, Sheng3; Tan, Zhangzhi3; Song, Ci1
刊名INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
出版日期2025-03-04
卷号39期号:3页码:510-532
关键词Spatially embedded networks spatial community modularity function spatially constrained Leiden resolution limit problem
ISSN号1365-8816
DOI10.1080/13658816.2024.2421778
产权排序3
文献子类Article
英文摘要Spatial community detection plays a crucial role in the analysis of spatially embedded networks. However, most existing methods adopt modularity as an objective function, which may fail to detect small spatial communities (i.e. the well-known resolution-limit problem). To alleviate this problem, a local network structure-based spatially constrained Leiden method was developed. First, the weights of the edges were reset based on the local network structure, which facilitated a clearer delineation between distinct communities. Second, we extended Leiden, an effective community detection method, to spatial community detection content by adding spatial constraints. Experiments on simulated datasets demonstrated that the proposed method is superior to four state-of-the-art methods for detecting spatial communities of different sizes. A case study conducted using the Shenzhen taxi dataset demonstrated that the proposed method outperformed four state-of-the-art methods in revealing urban spatial structures. Notably, the modularity of the spatial communities detected using the proposed method exhibited a marked improvement, nearly doubling that of the four comparative methods in the case study. This study presents a novel and promising framework for detecting spatial communities using modularity.
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WOS关键词PATTERNS
WOS研究方向Computer Science ; Geography ; Physical Geography ; Information Science & Library Science
语种英语
WOS记录号WOS:001346929000001
出版者TAYLOR & FRANCIS LTD
源URL[http://ir.igsnrr.ac.cn/handle/311030/212397]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Xing, Hanfa
作者单位1.State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
2.South China Normal Univ, Sch Geog, Guangzhou, Peoples R China;
3.South China Normal Univ, Beidou Res Inst, Foshan, Peoples R China;
推荐引用方式
GB/T 7714		 Liu, Wenkai,Cai, Haonan,Xing, Hanfa,et al. Alleviating the resolution limit problem in spatial community detection: a local network structure-based method[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2025,39(3):510-532.
APA Liu, Wenkai,Cai, Haonan,Xing, Hanfa,Hu, Sheng,Tan, Zhangzhi,&Song, Ci.(2025).Alleviating the resolution limit problem in spatial community detection: a local network structure-based method.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,39(3),510-532.
MLA Liu, Wenkai,et al."Alleviating the resolution limit problem in spatial community detection: a local network structure-based method".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 39.3(2025):510-532.

入库方式： OAI收割

来源：地理科学与资源研究所

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