An Efficient Heterogeneous Ontology Matching Technology

Recent years, with the rapid development of Internet technology and enhancement of the demand for network information by people, the researchers proposed the Semantic Web model. Semantic Web is the web with additional information called ontology. The emergence of heterogeneous ontologies, is caused by a variety of reasons:the autonomy of the network leads to multiple nodes manage ontologies respectively throughout the network; the difference of people's knowledge of the objective world, as well as the diversity of internal logic structures of ontology, will result in the heterogeneous ontologies describing the same domain. Therefore, to achieve the exchange of information between the different network nodes, we must resolve the heterogeneous problem between the different nodes. Currently, ontology mapping is one of most effective way to solve the problem of heterogeneous ontologies.In this paper, the contents of the study is to find a fast and efficient mapping algorithm for heterogeneous ontologies in the same field. This paper put forward a method of similarity calculation based on heterogeneous ontologies, considering the factors of similarity of literal meaning and semantic structure(including the depth of the node, node density, edge weight, information content, etc.) can get concept mapping between heterogeneous ontologies more accurate. Simultaneously, taking into account the optimization of mapping method, the speed of matching has also been improved to a large extent, the problem of how to improve the speed of matching more effectually has been mentioned in this paper. The experiment results show this method can effectively get better effectiveness with concept similarity computing, excluding the effects of heterogeneous ontologies.