Designing a novel cross ontology measure to extract resources from knowledge base for an adaptive e–learning system. (7th July 2014)

• Record Type: Journal Article
• Authors: Saleena, B.; Srivatsa, S.K.
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 9:Number 3(2014)
• Page Start: 193
• Page End: 203
• Publication Date: 2014-07-07
• Subjects: ontology -- similarity measure -- concept similarity -- WordNet -- MeSH -- semantics -- adaptive e–learning -- electronic learning -- online learning; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

E–Learning deals with the interaction between the teacher and learner on the basis of knowledge possessed by the learner. Ontology is a key concept that helps in providing more relevant and accurate information to the users for a particular domain or from multiple domains. Finding semantic similarity between the concepts of different ontologies will enhance the integration and retrieval of resources in a more meaningful way. In this paper, an adaptive e–learning system is proposed, which generates use r–specific e–learning contents based on their knowledge level and by comparing the similarity of concepts between ontologies. Based on this a new approach is designed to retrieve more relevant and accurate documents by embedding a new Concept Similarity measure (ConSim), after evaluating the user's knowledge based on the search query. The experimental results prove that after embedding the ConSim measure the retrieval results have been improved.