Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning 2020
DOI: 10.24963/kr.2020/51
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Plausible Reasoning about EL-Ontologies using Concept Interpolation

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 … Show more

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Cited by 2 publications
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“…However, it is difficult to relate degrees of similarity to the plausibility of the inferred rules in a principled way. For this reason, interpolation has been put forward as an alternative to similarity based reasoning [81][82][83]. The intuition is to start from a minimum of two rules e.g.…”
Section: Using Embeddings For Flexible Symbolic Reasoningmentioning
confidence: 99%
“…However, it is difficult to relate degrees of similarity to the plausibility of the inferred rules in a principled way. For this reason, interpolation has been put forward as an alternative to similarity based reasoning [81][82][83]. The intuition is to start from a minimum of two rules e.g.…”
Section: Using Embeddings For Flexible Symbolic Reasoningmentioning
confidence: 99%