Research On Approaches Of RFCA-based Ontology Mapping

Ontology mapping is a key technology to achieve 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. Mapping method has effect on efficiency of mapping and accuracy of mapping results, but also scale of ontology has effect on efficiency of mapping, the large of scale, the lower efficiency. Reducing the participation of expert is another aim of mapping. In the environment of semantic Web, in the absence of experts, we don't have any prior knowledge about whether there exist mapping between the two ontologies which can be obtained randomly. If we map the uncorrelated ontologies, we would waste more time on unnecessary work.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. And we also proposed a model of existence of mapping, and propose a method to judge the existence of mapping automatically. In the approach, we describe the model frame of existence of mapping and wordnet is used to judge the existence. With the decision making of mapping, we will decide which part of ontology is worth to mapping and which is not. The existence method will improve the mapping efficiency and avoid doing unnecessary work. Lastly, we use the RFCA model with attribute reduction and existence judgment to complete calculation of mapping.