Extending the Expression Ability of LAV Using Ontology Technique

Information fusion is an interdisciplinary research field aiming to combine and merge the information or data from different information sources. The output of information fusion system is a global schema through which users can get information or data from different dispersed sources. To generate a Deep Web information fusion system is facing many challenges, because the nature of Web is different from those of traditional databases and multi-databases. The major challenge in a Deep Web information fusion system is the data source modeling problem, which determine the technical method of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. We present an approach that the semantic relationships between semantic related attributes can be evaluated by the WordNet, a kind of ontology instrument. The experiment is carried out on the famous dataset, and the result shows the efficiency of ontology extended LAV of building mappings between local views and mediator schema.