A Hybrid Partitioning Based Parallel Ontology Reasoning Approach

Abstract

The ontology is usually the knowledge infrastructure for semantic Web and some intelligent systems. Ontology technology is one of the key technologies of the semantic Web. However, the performance of large-scale ontology reasoning has become one of the bottlenecks of the semantic Web based applications. We examine the problem of paralleling the reasoning process for ontology. A key challenge in the problem is partitioning the computational workload to minimize duplication of computation and data communicated among computing nodes. A hybrid partitioning based parallel ontology reasoning approach is proposed to address this challenge. Firstly, OWL ontology files were stored into the database in the form of triple table using Oracle 11g semantic technology. Secondly, a hybrid ontology partitioning approach, which combines both tuple partition and rule partition was designed and implemented. Thirdly, hybrid partitioning based ontology reasoning was achieved using parallel computing technology. Experimental results show that the parallel reasoning methods described herein can significantly improve reasoning performance.