ML Anthology

Using Qualitative Spatial Logic for Validating Crowd-Sourced Geospatial Data

Heshan Du, Hai H. Nguyen, Natasha Alechina, Brian Logan, Michael Jackson, John Goodwin
AAAI 2015 pp. 3948-3953
doi:10.1609/AAAI.V29I2.19052 /aaai/2015/du2015aaai-using/

Abstract

We describe a tool, MatchMaps, that generates sameAs and partOf matches between spatial objects (such as shops, shopping centres, etc.) in crowd-sourced and authoritative geospatial datasets. MatchMaps uses reasoning in qualitative spatial logic, description logic and truth maintenance techniques, to produce a consistent set of matches. We report the results of an initial evaluation of MatchMaps by experts from Ordnance Survey (Great Britain’s National Mapping Authority). In both the case studies considered, MatchMaps was able to correctly match spatial objects (high precision and recall) with minimal human intervention.

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Cite

Text

Du et al. "Using Qualitative Spatial Logic for Validating Crowd-Sourced Geospatial Data." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I2.19052

Markdown

[Du et al. "Using Qualitative Spatial Logic for Validating Crowd-Sourced Geospatial Data." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/du2015aaai-using/) doi:10.1609/AAAI.V29I2.19052

BibTeX

@inproceedings{du2015aaai-using,
  title     = {{Using Qualitative Spatial Logic for Validating Crowd-Sourced Geospatial Data}},
  author    = {Du, Heshan and Nguyen, Hai H. and Alechina, Natasha and Logan, Brian and Jackson, Michael and Goodwin, John},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {3948-3953},
  doi       = {10.1609/AAAI.V29I2.19052},
  url       = {https://mlanthology.org/aaai/2015/du2015aaai-using/}
}