Materialisation-Based Reasoning in DatalogMTL with Bounded Intervals

نویسندگان

چکیده

DatalogMTL is a powerful extension of Datalog with operators from metric temporal logic (MTL), which has received significant attention in recent years. In this paper, we investigate materialisation-based reasoning (a.k.a. forward chaining) the context programs and datasets bounded intervals, where partial representations canonical model are obtained through successive rounds rule applications. Although materialisation does not naturally terminate setting, it known that structure models ultimately periodic. Our first contribution paper detailed analysis periodic models; particular, formulate saturation conditions whose satisfaction by implies an ability to recover full via unfolding; allows us compute actual periods describing repeating parts as well establish concrete bounds on number applications required achieve saturation. Based these theoretical results, propose practical algorithm can be efficiently detected progresses, relevant used evaluate entailment queries unfolding computed. We have implemented our experiments suggest approach both scalable robust.

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ژورنال

عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence

سال: 2023

ISSN: ['2159-5399', '2374-3468']

DOI: https://doi.org/10.1609/aaai.v37i5.25807