Building Ontology Automatically Based on Bayesian Network and PART Neural Network

The deployment of the semantic Web depends on the rapid and efficient construction of the ontology. But traditional ontology construction is time-consuming and costly procedure. This paper present a novel ontology construction method based on ART network and Bayesian Network. The feature of this ontology construction system includes that the PART architecture overcomes the lack of flexibility in clustering, while in the Web page analysis, WordNet and Entropy deal with the lack of knowledge acquisition. The system then uses a Bayesian network to insert the terms and finish the complete hierarchy of the ontology. The experimental results indicate that this method has great promise.