[2312.08992] QQESPM: A Quantitative and Qualitative Spatial Pattern Matching Algorithm Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Databases arXiv:2312.08992 (cs) [Submitted on 14 Dec 2023 ( v1 ), last revised 27 May 2024 (this version, v2)] Title: QQESPM: A Quantitative and Qualitative Spatial Pattern Matching Algorithm Authors: Carlos Minervino , Claudio Campelo , Maxwell Oliveira , Salatiel Silva View a PDF of the paper titled QQESPM: A Quantitative and Qualitative Spatial Pattern Matching Algorithm, by Carlos Minervino and 3 other authors View PDF HTML (experimental) 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. Comments: DBLP Entry: this https URL Conference Repository: this http URL Accepted for the Brazilian Symposium on Geoinformatics (GEOINFO 2023) Subjects: Databases (cs.DB) Cite as: arXiv:2312.08992 [cs.DB] (or arXiv:2312.08992v2 [cs.DB] for this version) https://doi.org/10.48550/arXiv.2312.08992 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Proc. XXIV GEOINFO, pp. 261-272, 2023 Submission history From: Carlos V. A. Minervino Pontes [ view email ] [v1] Thu, 14 Dec 2023 14:40:57 UTC (738 KB) [v2] Mon, 27 May 2024 15:28:16 UTC (295 KB) Full-text links: Access Paper: View a PDF of the paper titled QQESPM: A Quantitative and Qualitative Spatial Pattern Matching Algorithm, by Carlos Minervino and 3 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.DB < prev | next > new | recent | 2023-12 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from