Exact Learning of Lightweight Description Logic Ontologies
From International Center for Computational Logic
Exact Learning of Lightweight Description Logic Ontologies
Boris KonevBoris Konev, Carsten LutzCarsten Lutz, Ana OzakiAna Ozaki, Frank WolterFrank Wolter
Boris Konev, Carsten Lutz, Ana Ozaki, Frank Wolter
Exact Learning of Lightweight Description Logic Ontologies
Journal of Machine Learning Research, 18:1-63, 2018
Exact Learning of Lightweight Description Logic Ontologies
Journal of Machine Learning Research, 18:1-63, 2018
- KurzfassungAbstract
We study the problem of learning description logic (DL) ontologies in Angluin et al.’s framework of exact learning via queries. We admit membership queries (“is a given subsumption entailed by the target ontology?”) and equivalence queries (“is a given ontology equivalent to the target ontology?”). We present three main results: (1) ontologies formulated in (two relevant versions of) the description logic DL-Lite can be learned with polynomially many queries of polynomial size; (2) this is not the case for ontologies formulated in the description logic EL, even when only acyclic ontologies are admitted; and (3) ontologies formulated in a fragment of EL related to the web ontology language OWL 2 RL can be learned in polynomial time. We also show that neither membership nor equivalence queries alone are sufficient in cases (1) and (3). - Projekt:Project: Cfaed
- Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems
@article{KLOW2018,
author = {Boris Konev and Carsten Lutz and Ana Ozaki and Frank Wolter},
title = {Exact Learning of Lightweight Description Logic Ontologies},
journal = {Journal of Machine Learning Research},
volume = {18},
year = {2018},
pages = {1-63}
}
