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

Authors

476

  1. KR
    Kirk Roberts

    The University of Texas Health Science Center at Houston, United States

    5 publications · 83 citations

    5

    h-index

  2. PK
    Parisa Kordjamshidi

    Michigan State University, United States

    4 publications · 234 citations

    4

    h-index

  3. MM
    Marie‐Francine Moens

    KU Leuven, Belgium

    4 publications · 237 citations

    4

    h-index

  4. AK
    Anastasios Kyrillidis

    École Polytechnique Fédérale de Lausanne, Switzerland

    3 publications · 47 citations

    3

    h-index

  5. DP
    Dieter Pfoser

    George Mason University, United States

    3 publications · 47 citations

    3

    h-index

1–5 of 476

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 158 citations

    6

    h-index

  2. 4

    h-index

  3. Pattern Recognition

    3 publications · 76 citations

    3

    h-index

  4. Neurocomputing

    3 publications · 41 citations

    3

    h-index

  5. Lirias (KU Leuven)

    Repository · 3 publications · 108 citations

    3

    h-index

1–5