Small Is Beautiful: Computing Minimal Equivalent EL Concepts

Authors

  • Nadeschda Nikitina University of Oxford
  • Patrick Koopmann University of Dresden

DOI:

https://doi.org/10.1609/aaai.v31i1.10684

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.

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Published

2017-02-12

How to Cite

Nikitina, N., & Koopmann, P. (2017). Small Is Beautiful: Computing Minimal Equivalent EL Concepts. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10684

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning