Exact Learning of Lightweight Description Logic Ontologies
This addresses the challenge of automating ontology construction for knowledge representation systems, with incremental theoretical advances in computational learning theory.
The paper tackles the problem of learning description logic ontologies exactly via queries, showing that DL-Lite ontologies can be learned with polynomially many queries, EL ontologies cannot even when acyclic, and a fragment of EL related to OWL 2 RL can be learned in polynomial time.
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).