An Ontology Mapping Method Based on Bayesian and Gaussian Model

In Semantic Web, Ontology mapping is the key to solving ontology heterogeneous. In this paper, a new ontology model based on Bayesian-Gaussian is proposed in the face of multiple ontology mapping. First of all, the method transforms the ontology model into a Bayesian network model. Then, based on traditional Bayesian network model, the hybrid Gaussian model is used to cluster the mixed node groups. Finally, iterative mapping mode is used to reduce the error. In the case of obtaining the similarity degree of the initial mapping node, the similarity degree of other similar similarity nodes is determined by the iterative module. The experimental results show that the IOBGM system presented in this paper has outstanding performance on ontology recall rate, and has certain application advantages in the case of multi-ontology mapping. Its stability and efficiency can meet the practical requirements.