On the Complexity of Learning Description Logic Ontologies

Abstract

Ontologies are a popular way of representing domain knowledge, in particular, knowledge in domains related to life sciences. (Semi-) automating the process of building an ontology has attracted researchers from different communities into a field called "Ontology Learning". We provide a formal specification of the exact and the probably approximately correct learning models from computational learning theory. Then, we recall from the literature complexity results for learning lightweight description logic (DL) ontologies in these models. Finally, we highlight other approaches proposed in the literature for learning DL ontologies.

Learning Description Logic Ontologies: Five Approaches. Where Do They Stand?

“…It has been shown that the EL fragments EL lhs and EL rhs -the EL fragments that allow only conjunctions of concept names on the right-side and on the left-side of CIs, respectively-are polynomial time exactly learnable from entailments [23,24,38,37] 4 , however, this is not the case for EL. The learning framework is the one in Example 1 and the problem statement is the same as in the original approach.…”