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Exact Learning of Lightweight Description Logic Ontologies

arXiv 1709.07314 ↗First posted 20 Sep 2017cs.LG cs.AI cs.LOcited by 10

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Abstract (arXiv)

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).

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2017.

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Citing papers per year: 2021: 4; 2022: 1; 2023: 2; 2024: 1; 2025: 1; 2026: 1.

10 papers.