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Graph-based Spatial Pattern Matching: A Theoretical Comparison

Published: 22 November 2024 Publication History

Abstract

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.

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  • (2024)Metric Reasoning in Large Language ModelsProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691226(501-504)Online publication date: 29-Oct-2024

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cover image ACM Conferences
SIGSPATIAL '24: Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems
October 2024
743 pages
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 22 November 2024

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Author Tags

  1. Spatial pattern matching
  2. complexity analysis
  3. graph pattern matching

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SIGSPATIAL '24 Paper Acceptance Rate 37 of 122 submissions, 30%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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  • (2024)Metric Reasoning in Large Language ModelsProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691226(501-504)Online publication date: 29-Oct-2024

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