Understanding the Spatial Complexity in Landscape Narratives Through Qualitative Representation of Space (Short Paper)

Authors Erum Haris , Anthony G. Cohn , John G. Stell



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Author Details

Erum Haris
  • School of Computing, University of Leeds, UK
Anthony G. Cohn
  • School of Computing, University of Leeds, UK
  • The Alan Turing Institute, London, UK
John G. Stell
  • School of Computing, University of Leeds, UK

Acknowledgements

We also thank the entire team of the Spatial Narratives project (https://spacetimenarratives.github.io/) for their discussions on the CLDW and this work.

Cite AsGet BibTex

Erum Haris, Anthony G. Cohn, and John G. Stell. Understanding the Spatial Complexity in Landscape Narratives Through Qualitative Representation of Space (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 37:1-37:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.37

Abstract

Narratives are the richest source of information about the human experience of place. They represent events and movement, both physical and conceptual, within time and space. Existing techniques in geographical text analysis usually incorporate named places with coordinate information. This is a serious limitation because many textual references to geography are ambiguous, non-specific, or relative. It is imperative but hard for a geographic information system to capture a text’s sense of place, an imprecise concept. This work aims to utilize qualitative spatial representation and natural language processing to allow representations of all three characteristics of place (location, locale, sense of place) as found in textual sources.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Knowledge representation and reasoning
Keywords
  • Narratives
  • Qualitative spatial representation
  • Natural language processing

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