Semantic Web (Berners-Lee, Hendler, & Lassila, 2001) focuses on effective management of documents intelligently which are present in the Web by considering the properties of the entities (terms) and the relationships involved among them. This conceptual organization is facilitated by building ontology pertaining to a particular domain (Gomez-Perez, Fernandez, & Corcho, 2003; Bateman, 2010). One of the major areas of research in retrieving the web information intelligently is the provision of learning course contents through online (E-learning) (Jegatha-Deborah, Baskaran, & Kannan, 2011). The prerequisite of the semantic-driven resource management and content delivery in E-learning web service has been facilitated in such systems by building Ontology.
Automatic exchanging and reusing of data or information in the universal medium for information exchange (WWW) is very limited due to two main reasons namely the heterogeneity problem prevailing in the information resources and the non-semantic nature of HTML and URL. Information heterogeneity occurs in syntax, structure and semantics. Though enhanced techniques are developed to solve syntactic and structural heterogeneity problems (Giunchiglia, Yatskevich, & Shvaiko, 2007), the problem of semantic heterogeneity is still prevailing to be a great challenge. When two contexts do not share the same interpretation of information, semantic heterogeneity occurs. Several approaches were proposed in the past (Doan et al., 2003) to solve semantic heterogeneity problems like synonym sets, concept lattices, features and constraints. However, all these existing approaches could solve this problem only partially.