C.Ramesh¹, K.V.Chalapati Rao¹, A.Govardhan², ¹CVR College of Engineering, India and ²JNT University, India

Today, the notion of Semantic Web has emerged as a prominent solution to the problem of organizing the immense information provided by World Wide Web, and its focus on supporting a better co-operation between humans and machines is noteworthy. Ontology forms the major component of Semantic Web in its realization. However, manual method of ontology construction is time-consuming, costly, error-prone and inflexible to change and in addition, it requires a complete participation of knowledge engineer or domain expert. To address this issue, researchers hoped that a semi-automatic or automatic process would result in faster and better ontology construction and enrichment. Ontology learning has become recently a major area of research, whose goal is to facilitate construction of ontologies, which reduces the effort in developing ontology for a new domain. However, there are few research studies that attempt to construct ontology from semi-structured Web pages. In this paper, we present a complete framework for ontology learning that facilitates the semi-automation of constructing and enriching web site ontology from semi structured Web pages. The proposed framework employs Web Content Mining and Web Usage mining in extracting conceptual relationship from Web. The main idea behind this concept was to incorporate the web author's ideas as well as web users’ intentions in the ontology development and its evolution.

Ontology Learning, Web Mining, Web Content Mining, Web Usage Mining, Ontology Evaluation