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Concept Induction refers to the problem of creating complex Description Logicclass descriptions (i.e., TBox axioms) from instance examples (i.e., ABoxdata). In this paper we look particularly at the case where both a set ofpositive and a set of negative instances are given, and complex classexpressions are sought under which the positive but not the negative examplesfall. Concept induction has found applications in ontology engineering, butexisting algorithms have fundamental performance issues in some scenarios,mainly because a high number of invokations of an external Description Logicreasoner is usually required. In this paper we present a new algorithm for thisproblem which drastically reduces the number of reasoner invokations needed.While this comes at the expense of a more limited traversal of the searchspace, we show that our approach improves execution times by up to severalorders of magnitude, while output correctness, measured in the amount ofcorrect coverage of the input instances, remains reasonably high in many cases.Our approach thus should provide a strong alternative to existing systems, inparticular in settings where other systems are prohibitively slow.

Efficient Concept Induction for Description Logics