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Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.COSIT.2022.18
URN: urn:nbn:de:0030-drops-169039
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16903/
Beydokhti, Mohammad Kazemi ;
Duckham, Matt ;
Tao, Yaguang ;
Vasardani, Maria ;
Griffin, Amy
Qualitative Spatial Reasoning over Questions (Short Paper)
Abstract
Although geospatial question answering systems have received increasing attention in recent years, existing prototype systems struggle to properly answer qualitative spatial questions. In this work, we propose a unique framework for answering qualitative spatial questions, which comprises three main components: a geoparser that takes the input questions and extracts place semantic information from text, a reasoning system which is embedded with a crisp reasoner, and finally, answer extraction, which refines the solution space and generates final answers. We present an experimental design to evaluate our framework for point-based cardinal direction calculus (CDC) relations by developing an automated approach for generating three types of synthetic qualitative spatial questions. The initial evaluations of generated answers in our system are promising because a high proportion of answers were labelled correct.
BibTeX - Entry
@InProceedings{beydokhti_et_al:LIPIcs.COSIT.2022.18,
author = {Beydokhti, Mohammad Kazemi and Duckham, Matt and Tao, Yaguang and Vasardani, Maria and Griffin, Amy},
title = {{Qualitative Spatial Reasoning over Questions}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {18:1--18:7},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-257-0},
ISSN = {1868-8969},
year = {2022},
volume = {240},
editor = {Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2022/16903},
URN = {urn:nbn:de:0030-drops-169039},
doi = {10.4230/LIPIcs.COSIT.2022.18},
annote = {Keywords: Qualitative spatial reasoning, geospatial question answering, Qualitative spatial questions}
}
