Plausible reasoning about EL-Ontologies using concept interpolation

Ibanez Garcia, Yazmin ORCID: https://orcid.org/0000-0002-1276-904X, Gutierrez Basulto, Victor ORCID: https://orcid.org/0000-0002-6117-5459 and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2020. Plausible reasoning about EL-Ontologies using concept interpolation. Presented at: 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), Rhodes, Greece, 12-18 September 2020. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning. IJCAI Organization, pp. 506-516. 10.24963/kr.2020/51

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Abstract

Description logics (DLs) are standard knowledge representation languages for modelling ontologies, i.e. knowledge about concepts and the relations between them. Unfortunately, DL ontologies are difficult to learn from data and time-consuming to encode manually. As a result, ontologies for broad domains are almost inevitably incomplete. In recent years, several data-driven approaches have been proposed for automatically extending such ontologies. One family of methods rely on characterizations of concepts that are derived from text descriptions. While such characterizations do not capture ontological knowledge directly, they encode information about the similarity between different concepts that can be exploited for filling in the gaps in existing ontologies. To this end, several inductive inference mechanisms have already been proposed, but these have been defined and used in a heuristic fashion. In this paper, we instead propose an inductive inference mechanism which is based on a clear model-theoretic semantics, and can thus be tightly integrated with standard deductive reasoning. We particularly focus on interpolation, a powerful commonsense reasoning mechanism which is closely related to cognitive models of category-based induction. Apart from the formalization of the underlying semantics, as our main technical contribution we provide computational complexity bounds for reasoning in EL with this interpolation mechanism.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	IJCAI Organization
Funders:	ERC Starting Grant 637277
Date of First Compliant Deposit:	3 July 2020
Date of Acceptance:	3 June 2020
Last Modified:	04 Sep 2025 14:30
URI:	https://orca.cardiff.ac.uk/id/eprint/132974

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