A survey on geocoding: algorithms and datasets for toponym resolution.

Geocoding, the task of converting unstructured text to structured spatial data, has recently seen progress thanks to a variety of new datasets, evaluation metrics, and machine-learning algorithms. Geocoding plays a critical role in tasks such as tracking the evolution and emergence of infectious dis...

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Published in:Language Resources & Evaluation Vol. 59; no. 2; pp. 1775 - 1797
Main Authors: Zhang, Zeyu, Bethard, Steven
Format: Literature Review
Published: Springer Nature Jun2025
Subjects:
Online Access:View this record in EBSCOhost
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        atl: A survey on geocoding: algorithms and datasets for toponym resolution.
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        au:
          Zhang, Zeyu
          Bethard, Steven
        affil: https://ror.org/03m2x1q45 School of Information, University of Arizona, 1103 E. 2nd St., 85721, Tucson, AZ, USA
      su:
        Artificial intelligence
        Machine learning
        Emergency management
        Image processing
        Communicable diseases
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        subj:
          Artificial intelligence
          Machine learning
          Emergency management
          Image processing
          Communicable diseases
      keyword:
        Geocoding
        Geographical entity normalization
        Information and Computing Sciences Artificial Intelligence and Image Processing
        Toponym resolution
      ab: Geocoding, the task of converting unstructured text to structured spatial data, has recently seen progress thanks to a variety of new datasets, evaluation metrics, and machine-learning algorithms. Geocoding plays a critical role in tasks such as tracking the evolution and emergence of infectious diseases, analyzing and searching documents by geography, geospatial analysis of historical events, and disaster response mechanisms. To assist those new to this area of research, we provide a survey that reviews, organizes and analyzes recent work on geocoding (also known as toponym resolution) where text is matched to geospatial coordinates and/or ontologies. We summarize the findings of this research, including the domains and databases covered by current geocoding corpora, point-based and polygon-based evaluation metrics, and features and architectures of geocoding systems.
      pubtype: Academic Journal
      doctype: Literature Review
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    language: English
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