Applications of expressive ontology reasoning for the Semantic Web require scalable algorithms for deducing implicit knowledge from explicitly given knowledge bases. Besides the development of more effi- cient such algorithms, awareness is rising that approximate reasoning solutions will be helpful and needed for certain application domains. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on experiments which show that a significant gain in efficiency can be achieved.
& Hitzler, P.
(2008). Approximate OWL-Reasoning with Screech. Lecture Notes in Computer Science, 5341, 165-180.