A Semantic Web Information Integration System Based on Ontology-Mapping and Multilevel Query Interface

Abstract

The Semantic Web has introduced various distributed and dynamically increasing knowledge bases that are built on formal logic. At present, however, each knowledge base has merely a certain or some limited types of information, which are insufficient in consideration that users demands may involve extra information in most cases. Moreover, current knowledge bases are generally constructed on a mixture of ontologies, which more or less cause difficulties in the searching and integration of semantic data. Besides, a great majority of users are incapable of utilizing semantic searching. Above all, therefore, this study designed and implemented a system that allows different groups of users to query semantic information from multiple sources through a unified user-friendly interface by introducing a multilevel searching interface, which provides four fundamental input methods that allows users to generate formal query as well as proposing a processing method that achieves ontology mapping, automatic searching and integration of data from different knowledge bases. The evaluation experiments were conducted and the results of which showed that the usability and performance of our system are reasonable.