Plausible Reasoning about EL-Ontologies using Concept Interpolation
Yazm\'in Ib\'a\~nez-Garc\'ia, V\'ictor Guti\'errez-Basulto, Steven, Schockaert

TL;DR
This paper introduces a formal, model-theoretic approach to concept interpolation in EL-ontologies, enhancing automatic ontology extension with a clear reasoning framework and complexity analysis.
Contribution
It proposes a novel, semantics-based inference mechanism for EL-ontologies using concept interpolation, integrating it with standard reasoning and providing complexity bounds.
Findings
Formal semantics for concept interpolation in EL
Complexity bounds for reasoning with interpolation
Enhanced methods for automatic ontology extension
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, which 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…
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