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Communication Dans Un Congrès Année : 2022

An Incremental Algorithm for Handling Qualitative Spatio-Temporal Information

Zhiguo Long
Qiyuan Hu
Hua Meng
Michael Sioutis

Résumé

In this paper, we present an online (incremental) algorithm for checking the satisfiability of qualitative spatio-temporal data, with direct implications to other fundamental knowledge representation and reasoning problems for such data, like the problems of deductive closure and redundancy removal. In particular, qualitative data come in the form of human-like, symbolic, descriptions such as "region x contains or overlaps region y", which are abundant in the Web of Data. Our approach is also able to maintain, to some extent, any sparse graph structure that may be inherent in the data, i.e., it acts parsimoniously and only tries to infer new information when needed for soundness and completeness. To this end, we complement our practical algorithm with certain theoretical results to assert its correctness and efficiency. A subsequent evaluation with publicly available large-scale real-world and random datasets against the state of the art, shows the interest and promise of our method.
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Dates et versions

hal-04290667 , version 1 (17-11-2023)

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Zhiguo Long, Qiyuan Hu, Hua Meng, Michael Sioutis. An Incremental Algorithm for Handling Qualitative Spatio-Temporal Information. 15th International Conference on Spatial Information Theory (COSIT 2022), Sep 2022, Kobe, Japan. ⟨10.4230/LIPICS.COSIT.2022.5⟩. ⟨hal-04290667⟩
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