Towards Mapping Large Scale Ontologies Based on RFCA with Attribute Reduction

Ontology mapping is one of the most fundamental issues to address the interoperability between heterogeneous and distributed ontologies. So far, many efforts have been conducted to suggest ontology mapping models. The RFCA mapping model is one of potential them. However, how to construct relationship among the large scale ontologies is also one of challenges concerning the semantic web world. This paper addresses the problem of the reduction of formal context in the mapping process of the RFCA model to adapt the large scale ontologies. Based on this issue, a method using attribute reduction to enhance the RFCA ontology mapping method is proposed. Using attribute reduction technology, the RFCA method can be adaptable to the large scale of ontology mapping. A prototype has implemented based on this method. The results of experiments show that this method is potential method to adaptable to the large scale of ontology engineering.