Parallelization of ontology construction and fusion based on MapReduce

As a data integration technology, ontology has been widely used in the knowledge systems and domain knowledge representation. An ontology construction and fusion technology for large-scale data is very important. In this paper, we propose a parallel ontology construction and fusion approach adapted to MapReduce framework based on the traditional ontology technology and MapReduce. The method separates the ontology model building process from the repeated calculation processes, and realizes the massive data integration. The evaluations tested on scientific literature data show the feasibility and efficiency of our approach.