The Research Of View-Based Ontology Mapping In The Semantic Web

The Semantic Web is the expansion of existing Web, its goal is to enable the information on the Web have semantics which computer can understand. But ontology describes these semantics, and it plays the vital role in the Semantic Web. As a result of the Semantic Web distributional characteristic, a large number of data are coming from different ontologies inevitably, but in the integration of heterogeneous ontologies, ontology mapping is the essential part.The mapping between global ontology and local ontology belongs to one kinds of ontology mappings, it defines that the concept and relations in the global ontology how to correspond to the concept and relations in the local ontology at the semantic level. Although "the mapping between the global ontology and local ontology" is the key of the Web integration, but so far it also lacks profound researches. In the accustomed ontology mapping methods, most are restricted at the relationships expression between two terms ,and lack essential application modes, so in the actual questions we need the more powerful support.Many techniques have been proved among the investigations of ontology mapping, after comparing and analyzing, a view-based ontology mapping method was proposed in this paper. The ontology view was actually the extraction of ontology, namely an application mode of ontology. As the reflection of user knowledge, it not only can make ontology mapping comprehensible and clear, but also can simplify uses information retrieval. An ontology mapping prototype system based on this method has been designed and partial implemented. Firstly local ontology views were constructed; secondly local view classes were clustered according to their semantic relationships, after local view classes were integrated into the global view class, the global ontology view and the bidirectional mapping relationships between global ontology view and local ontology views were constructed. Therefore the information search and localization are more accurate and fast, and the extensionality of mapping relationships is enhanced, moreover the ontology mapping is more suitable for dynamic informationenvironment.