An Integrated Solution for Improving Semantic Content Searching in Distributed Environment

The research in the ontology-based information retrieval has made a significant progress recently, especially in the Web domain. In this kind of retrieval system, the domain ontology is used as the backbone of the searching process. However, with the heterogeneity of data storing formats on the Web, many of ontology-driven systems development approach suffer from inconsistencies during mapping between ontologypsilas concepts and corresponding data from data sources. Thus, sophisticated data integration and mining tools are required so domain scientists can more easily retrieve answers to their queries. To address these requirements, we have proposed a Web content query refinement framework integrating both ontology and Web mining techniques to assist the material domain scientists. We used the Web ontology language (OWL) to represent structured knowledge about materials. We have used SWRL, the semantic Web rule language, as a high-level query language that uses the implemented OWL based mappings method. The main merit of our proposed solution is that the user can interactively process (accept or reject) the knowledge gathered during the mining process to enrich the ontology base (ontology learning), which leads to better query precision. We present an evaluation study using Query&Navi, to show the benefit of the proposed approach.