Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia

Emily Gao, Dominic Widdows

Abstract

As a tech company, Grab has expanded from transportation to food delivery, aiming to serve Southeast Asia with hyperlocalized applications. Information about places as transportation destinations can help to improve our knowledge about places as restaurants, so long as the spatial entity resolution problem between these datasets can be solved. In this project, we attempted to recognize identical place entities from databases of Points-of-Interest (POI) and GrabFood restaurants, using their spatial and textual attributes, i.e., latitude, longitude, place name, and street address. Distance metrics were calculated for these attributes and fed to tree-based classifiers. POI-restaurant matching was conducted separately for Singapore, Philippines, Indonesia, and Malaysia. Experimental estimates demonstrate that a matching POI can be found for over 35% of restaurants in these countries. As part of these estimates, test datasets were manually created, and RandomForest, AdaBoost, Gradient Boosting, and XGBoost perform well, with most accuracy, precision, and recall scores close to or higher than 90% for matched vs. unmatched classification. To the authors’ knowledge, there are no previous published scientific papers devoted to matching of spatial entities for the Southeast Asia region.

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Paper Citation


in Harvard Style

Gao E. and Widdows D. (2020). Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia.In Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-425-1, pages 92-103. DOI: 10.5220/0009416600920103


in Bibtex Style

@conference{gistam20,
author={Emily Gao and Dominic Widdows},
title={Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia},
booktitle={Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2020},
pages={92-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009416600920103},
isbn={978-989-758-425-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Spatial Entity Resolution between Restaurant Locations and Transportation Destinations in Southeast Asia
SN - 978-989-758-425-1
AU - Gao E.
AU - Widdows D.
PY - 2020
SP - 92
EP - 103
DO - 10.5220/0009416600920103