Abstract
Ontology is a kind of philosophical study which is dealing with nature being. Ontologies are extremely useful tools for different purpose and various modalities in different areas and communities. A common ontology is very effective in sophisticated software engineering purpose. In realistic world new meaningful words are always improving a language and to enhance the most widely used ontologies it requires mapping. To assure the quality manual mapping is used with some limitation. Partial automated mapping may apply to extend ontology by extracting and integrating knowledge from existing resources more effectively. In this paper, we present a semi-automated method, type of machine learning to enrich an existing ontology. Moreover, the approach can save time and ensure the accuracy that they need to serve.
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Acknowledgment
First of all we would like to show our gratitude to the Almighty, who gave us the effort to work on this project. We want to thanks our honorable supervisor Bayzid Ashik Hossain for guiding us. His profound knowledge in this field, keen interest, patience and continuous support lead to the completion of our work. His instructions have contributed greatly in every aspect of the thesis.
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Hasan, M.J., Badhan, A.I., Ahmed, N.I. (2019). Enriching Existing Ontology Using Semi-automated Method. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 886. Springer, Cham. https://doi.org/10.1007/978-3-030-03402-3_32
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DOI: https://doi.org/10.1007/978-3-030-03402-3_32
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