|Title||Distributed Reasoning with EL++ Using MapReduce|
|Year of Publication||2010|
|Authors||Maier, F, Mutharaju, R, Hitzler, P|
|Institution||Wright State University|
|City||Dayton, OH, USA|
It has recently been shown that the MapReduce framework for distributed computation can be used effectively for large-scale RDF Schema reasoning, computing the deductive closure of over a billion RDF triples within a reasonable time . Later work has carried this approach over to OWL Horst . In this paper, we provide a MapReduce algorithm for classifying knowledge bases in the description logic EL++, which is essentially the OWL 2 profile OWL 2 EL. The traditional EL++ classification algorithm is recast into a form compatible with MapReduce, and it is shown how the revised algorithm can be realized within the MapReduce framework. An analysis of the circumstances under which the algorithm can be effectively used is also provided.