Hypergraph-Based Inference Rules for Computing $$\mathcal{EL}\mathcal{}^+$$-Ontology Justifications

Autor: Hui Yang, Yue Ma, Nicole Bidoit
Rok vydání: 2022
Zdroj: Automated Reasoning ISBN: 9783031107689
DOI: 10.1007/978-3-031-10769-6_19
Popis: To give concise explanations for a conclusion obtained by reasoning over ontologies, justifications have been proposed as minimal subsets of an ontology that entail the given conclusion. Even though computing one justification can be done in polynomial time for tractable Description Logics such as $$\mathcal{EL}\mathcal{}^+$$ EL + , computing all justifications is complicated and often challenging for real-world ontologies. In this paper, based on a graph representation of $$\mathcal{EL}\mathcal{}^+$$ EL + -ontologies, we propose a new set of inference rules (called H-rules) and take advantage of them for providing a new method of computing all justifications for a given conclusion. The advantage of our setting is that most of the time, it reduces the number of inferences (generated by H-rules) required to derive a given conclusion. This accelerates the enumeration of justifications relying on these inferences. We validate our approach by running real-world ontology experiments. Our graph-based approach outperforms PULi [14], the state-of-the-art algorithm, in most of cases.
Databáze: OpenAIRE