Abstract
In this paper, we present our approach to build domain ontology for e-learning purposes from heterogeneous documents by using the automatic extraction technique. Ontologies have been frequently employed in order to solve problems for shared distributed knowledge and the effective integration of information across many applications. The process of ontology building is a very lengthy and error-prone work. Therefore, a number of research studies to build ontologies semi-automatically from existing documents have been developed. This paper proposes a novel method which is used to build ontology, using the existing knowledge base of heterogeneous documents for complex application domains without the need of human intervention. This method improves the system performance and accuracy and reduces the time for the ontology building process from a collection of documents.
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Jeslin Shanthamalar, J., Rene Robin, C.R. (2014). Automatic Ontology Extraction from Heterogeneous Documents for E-Learning Applications. In: Mohapatra, D.P., Patnaik, S. (eds) Intelligent Computing, Networking, and Informatics. Advances in Intelligent Systems and Computing, vol 243. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1665-0_66
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DOI: https://doi.org/10.1007/978-81-322-1665-0_66
Publisher Name: Springer, New Delhi
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