Approximating Description Logic Classification for Semantic Web Reasoning

In many application scenarios, the use of the Web ontology language OWL is hampered by the complexity of the underlying logic that makes reasoning in OWL intractable in the worst case. In this paper, we address the question whether approximation techniques known from the knowledge representation literature can help to simplify OWL reasoning. In particular, we carry out experiments with approximate deduction techniques on the problem of classifying new concept expressions into an existing OWL ontology using existing Ontologies on the web. Our experiments show that a direct application of approximate deduction techniques as proposed in the literature in most cases does not lead to an improvement and that these methods also suffer from some fundamental problems.