A novel approach for similarity and indexing-based ontology for semantic web educational system. (2016)

• Record Type: Journal Article
• Authors: Reddy, A. Brahmananda; Govardhan, A.
• Is Part Of: International journal of intelligent engineering informatics. Volume 4:Number 2(2016)
• Page Start: 117
• Page End: 134
• Publication Date: 2016
• Subjects: intelligent agents -- ontologies -- semantic web -- similarity indexing -- ontology-based information retrieval -- vector space model -- least common superconcept -- multi-agent modelling -- multi-agent systems -- MAS -- agent-based systems -- web content -- distance education -- online courses -- e-learning -- electronic learning -- online learning; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

Several web-based educational systems have been designed and widely used for the past two decades. However, there are some limitations in the previous systems. The integration of semantic web and artificial intelligence explores new methods for educational concepts. For instance, an educational system based on the semantic web (ESBSW) which represents the content and the knowledge in the form of ontology and counts on intelligent agents that allow machines to understand the web content. In this paper, a new approach for an educational system based on the semantic web is developed. The architecture of the system and the new mechanism for similarity and indexing based on ontology is proposed and elaborated. This paper also compares the performance evaluation of indexing system in the vector space model (VSM) and ontology-based information retrieval models. The similarity between the concept and document is calculated using semantic similarity measure.