QQESPM: A Quantitative and Qualitative Spatial Pattern Matching Algorithm
Carlos Minervino, Claudio Campelo, Maxwell Oliveira, Salatiel Silva

TL;DR
This paper introduces QQESPM, an algorithm extending spatial pattern matching to include connectivity constraints, improving retrieval of POIs based on spatial and connectivity criteria.
Contribution
It proposes a novel QQESPM algorithm that incorporates connectivity constraints into spatial pattern matching, extending existing methods.
Findings
QQESPM outperforms baseline approaches in efficiency.
The algorithm effectively handles connectivity constraints.
Performance tests validate QQESPM's superiority.
Abstract
The Spatial Pattern Matching (SPM) query allows for the retrieval of Points of Interest (POIs) based on spatial patterns defined by keywords and distance criteria. However, it does not consider the connectivity between POIs. In this study, we introduce the Qualitative and Quantitative Spatial Pattern Matching (QQ-SPM) query, an extension of the SPM query that incorporates qualitative connectivity constraints. To answer the proposed query type, we propose the QQESPM algorithm, which adapts the state-of-the-art ESPM algorithm to handle connectivity constraints. Performance tests comparing QQESPM to a baseline approach demonstrate QQESPM's superiority in addressing the proposed query type.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
