01230nas a2200133   4500008004100000245005200041210005000093260004500143520075900188100002100947700002300968700002000991856008501011       2010                        eng d00aDistributed Reasoning with EL++ Using MapReduce0 aDistributed Reasoning with EL Using MapReduce  aDayton, OH, USAbWright State University3 a<p>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 [23]. Later work has carried this approach over to OWL Horst [22]. 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.</p>
1 aMaier, Frederick1 aMutharaju, Raghava1 aHitzler, Pascal  uhttps://daselab.cs.ksu.edu/publications/distributed-reasoning-el-using-mapreduce