A skeleton extraction method for large-scale spatial interaction networks considering spatial distribution characteristics
文献类型：期刊论文
| 作者 | Zhang, Zheng2,3; Zhou, Chenghu2; Chen, Minjie3; Fan, Shaojing1 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2025-02-03 |
| 卷号 | N/A |
| 关键词 | Network skeleton network node importance network simplification spatial interaction networks |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2025.2460055 |
| 产权排序 | 2 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Constructing spatial interaction (SI) networks from massive geographic flow data is an important method for understanding the correlation patterns and trends among regions. However, large-scale SI networks usually cause complex edge interleaving and a sharp increase in noise information. A network skeleton can represent the key structure of the corresponding complex network with generalized network data. However, the existing extraction methods only consider the topological information of networks and ignore spatial information, which may cause difficulty maintaining the spatial distribution characteristics and the exclusion of key spatial information. To address the issue, we have developed a skeleton extraction method for large-scale SI networks. First, the network nodes are divided into different clusters via adaptive spatial clustering. Second, an entropy weight method is used to define a comprehensive evaluation indicator of the network node importance, and the nodes in each cluster are sorted and selected according to the comprehensive evaluation indicator. Finally, the skeleton structure of the SI network is reconstructed according to the selected nodes and their adjacent edges. Compared with the existing methods for extracting network skeletons, the proposed method can maintain the spatial distribution characteristics of SI networks while preserving key topological features. |
| URL标识 | 查看原文 |
| WOS关键词 | BACKBONE |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001412997000001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212336]  |
| 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 | Zhang, Zheng |
| 作者单位 | 1.Zhengzhou Planning Survey Design & Res Inst, Zhengzhou, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China; 3.Informat Engn Univ, Inst Geog Space Informat, Zhengzhou, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhang, Zheng,Zhou, Chenghu,Chen, Minjie,et al. A skeleton extraction method for large-scale spatial interaction networks considering spatial distribution characteristics[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2025,N/A. |
| APA | Zhang, Zheng,Zhou, Chenghu,Chen, Minjie,&Fan, Shaojing.(2025).A skeleton extraction method for large-scale spatial interaction networks considering spatial distribution characteristics.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,N/A. |
| MLA | Zhang, Zheng,et al."A skeleton extraction method for large-scale spatial interaction networks considering spatial distribution characteristics".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE N/A(2025). |
入库方式： OAI收割
来源：地理科学与资源研究所
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