Spatial Relation Extraction
Spatial Relation Extraction is a natural language processing task that identifies and classifies spatial relationships between geographic entities in text by specifying their directional, topological, or metric configurations within a given spatial context.
145
Publications
5.8K
Citations
476
Authors
203
Institutions
Publications per year
2017–2026
58
145
1–5 of 145
476
The University of Texas Health Science Center at Houston, United States
5 publications · 83 citations
5
h-index
4
h-index
4
h-index
École Polytechnique Fédérale de Lausanne, Switzerland
3 publications · 47 citations
3
h-index
3
h-index
1–5 of 476
203
KU Leuven
Leuven, Belgium
5 h-index
13 publications
729 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
4 h-index
6 publications
741 citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
4 h-index
8 publications
145 citations
Nanjing Normal University
Nanjing, China
4 h-index
15 publications
447 citations
The University of Texas Health Science Center at Houston
Houston, United States
4 h-index
11 publications
205 citations
George Mason University
Fairfax, United States
3 h-index
3 publications
47 citations
China University of Geosciences
Wuhan, China
3 h-index
15 publications
419 citations
Wuhan University
Wuhan, China
3 h-index
8 publications
462 citations
1–8 of 203
Repository · 6 publications · 158 citations
6
h-index
4 publications · 100 citations
4
h-index
3 publications · 76 citations
3
h-index
3 publications · 41 citations
3
h-index
Repository · 3 publications · 108 citations
3
h-index
1–5