Research on method of multi-ontology mapping based on concept classification
基于概念分类的多本体映射方法研究*

To improve the efficiency of ontology mapping with large scale multi-ontology, this paper proposed a method of multi-ontology mapping based on concept classification (MMBCC). It transformed the problem of large scale ontology participation into concept classification problems. Granular computing and semantic similarity computation based on WordNet were property of the classification trees, realized the process of concept classification by quick sort algorithm. Experiments show that the proposed method guarantees the accuracy while reducing the mapping number of comparisons of concept, reducing the complexity, and the method is feasible.