Small Is Beautiful: Computing Minimal Equivalent EL Concepts
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
In this paper, we present an algorithm and a tool for computing minimal, equivalent EL concepts wrt. a given ontology. Our tool can provide valuable support in manual development of ontologies and improve the quality of ontologies automatically generated by processes such as uniform interpolation, ontology learning, rewriting ontologies into simpler DLs, abduction and knowledge revision. Deciding whether there exist equivalent EL concepts of size less than k is known to be an NP-complete problem. We propose a minimisation algorithm that achieves reasonable computational performance also for larger ontologies and complex concepts. We evaluate our tool on several bio-medical ontologies with promising results.
Details
Original language | English |
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Title of host publication | Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence |
Publisher | AAAI Press |
Pages | 1206–1212 |
Publication status | Published - 2017 |
Peer-reviewed | Yes |