Graph-based Spatial Pattern Matching: A Theoretical Comparison
Published in 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2024
Spatial Pattern Matching is an important search problem that involves reasoning about the relative position, distance, and orientation of objects with respect to one another. Spatial relationships between objects contain a lot of information about the world, which makes them useful in applications like Point of Interest (POI) retrieval and location-based services. However, spatial pattern matching is an NP-hard problem in the worst case. This paper presents a theoretical comparison of spatial pattern matching approaches, showing how the prominent methods compare for each type of spatial relation they support. We further highlight the common techniques used to gain performance improvements and provide suggestions towards developing approximate solutions to this form of spatial search.
@inproceedings{schneider2024c,
title={Graph-based Spatial Pattern Matching: A Theoretical Comparison},
author={Schneider, Nicole R and O'Sullivan, Kent and Samet, Hanan},
booktitle={Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems},
pages={505--508},
year={2024}
}