Resource association discovery in semantic Web

Abstract

Resources on the Web have direct and hidden relations. Direct relations mean the visible link between two resources like hyperlinks. Direct relations are easy to discover while hidden relations are not. Current discovery methods are mostly based on the text learning and user feedback methods. The text contents are not fit for inference and they are also lack of semantics. The Web pages are annotated with ontologies in semantic Web. The annotations are useful for inference. We propose a framework for resource association discovery in semantic Web. The framework uses the annotation for inference and the annotation hierarchy can be solved by mapping different ontologies. The experiment shows the satisfied results. Finally, the conclusion and future work are discussed