Explaining Non-Entailment by Model Transformation for the Description Logic EL
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Reasoning results computed by description logic systems can be hard to comprehend. When an ontology does not entail an expected subsumption relationship, generating an explanation of this non-entailment becomes necessary. In this paper, we use countermodels to explain non-entailments. More precisely, we devise relevant parts of canonical models of EL ontologies that serve as explanations and discuss the computational complexity of extracting these parts by means of model transformations. Furthermore, we provide an implementation of these transformations and evaluate it using real ontologies.
Details
Originalsprache | Englisch |
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Titel | IJCKG '22: Proceedings of the 11th International Joint Conference on Knowledge Graphs |
Redakteure/-innen | Alessandro Artale, Diego Calvanese, Haofen Wang, Xiaowang Zhang |
Seiten | 1-9 |
Seitenumfang | 9 |
ISBN (elektronisch) | 9781450399876 |
Publikationsstatus | Veröffentlicht - 13 Feb. 2023 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | IJCKG: International Joint Conference on Knowledge Graphs |
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Externe IDs
Scopus | 85148543350 |
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dblp | conf/jist/AlrabbaaH22 |
Mendeley | 8c330099-4ff9-3904-a1a2-76a5bafba995 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Model Transformation, Explainable AI, Description Logics