Optimization of RDF reasoning based on MapReduce

With the development of information technology, the resource description framework (RDF) occupies very important position in structure of the semantic web. An effective way to enhance the efficiency of the RDF data query is RDF closures. Our work is improve the RDF reasoning in MapReduce framework. The algorithm is based on packet classification efficiency of a few of candidate rules, as well as the NoSQL data storage avoiding repetition, corresponding to the RDF properties and concepts. The optimization algorithm of MapReduce is given a new closure generation process. Our approach use RDFS inference rules and the RDF triples in relationship between Map and Reduce operations and generate the RDF closures, improve the generate efficiency of closure. Based on RDF MapReduce algorithm for RDF closure, look forward more suitable RDF closure computing scheme on cloud computing environment.