Web Resource Categorization by Detecting Potential Relations

Abstract

Since Semantic Web is increasing in size and variety of resources, it is difficult for users to find the information that they really need. Therefore, it is necessary to provide an efficient and precise method without explicit specification for the Web resources. In this paper, we proposed the novel approach of integrating four processes for Web resource categorization. The processes can extract both the explicit relations extracted from the ontologies in a traditional way and the potential relations inferred from existing ontologies by focusing on some new challenges such as extracting important class names, using WordNet relations and detecting the methods of describing the Web resources. We evaluated the effectiveness by applying the categorization method to a Semantic Web search system, and confirmed that our proposed method achieves a notable improvement in categorizing the valuable Web resources based on incomplete ontologies.