Graph-Based Spatial Clustering is a spatial clustering method that represents spatial entities as nodes and their relationships as edges in a graph structure, enabling the detection of clusters through graph partitioning or community detection algorithms based on topological connectivity.
27
Publications
1.6K
Citations
88
Authors
52
Institutions
Publications per year
2017–2026
13
Parents
Publications
27
Cell clustering for spatial transcriptomics data with graph neural networks
Jiachen Li, Siheng Chen, Xiaoyong Pan et al. · Nature Computational Science · 2022 · 225 citations
Clustering objects on a spatial network
Man Lung Yiu, Nikos Mamoulis · 2004 · 134 citations
Clustering Algorithms for Spatial Databases: A Survey
Erica Kolatch · 2001 · 87 citations
Computing, Geoinformatics, Geographic Information Science +11
1–5 of 27
Authors
88
- KL
2
h-index
- KA
2
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- ZY
2
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- SL
2
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- JW
2
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1–5 of 88
Institutions
52
Wuhan University of Technology
Wuhan, China
2 h-index
4 publications
224 citations
University of Stuttgart
Stuttgart, Germany
2 h-index
2 publications
60 citations
Liverpool John Moores University
Liverpool, United Kingdom
2 h-index
11 publications
627 citations
University of Calgary
Calgary, Canada
2 h-index
5 publications
289 citations
State Development & Investment Corporation (China)
Beijing, China
1 h-index
1 publications
47 citations
Nanjing Normal University
Nanjing, China
1 h-index
1 publications
25 citations
Digital Wave (United States)
Centennial, United States
1 h-index
1 publications
14 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
15 citations
1–8 of 52
Venues
- International Journal of Geographical Information Systems
2 publications · 107 citations
2
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- Procedia Computer Science
1 publications · 12 citations
1
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- Expert Systems with Applications
1 publications · 45 citations
1
h-index
- Transactions in GIS
1 publications · 22 citations
1
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- mBio
1 publications · 56 citations
1
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1–5