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Ontology Modelling for Metallurgy as a Domain and Retrieval Using Particle Swarm Optimization: Conceptualization, Modeling, and Retrieval
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Author(s): Gerard Deepak (National Institute of Technology, Tiruchirappalli, India), Ayush Kumar A. (National Institute of Technology, Tiruchirappalli, India), Santhanavijayan A. (National Institute of Technology, Tiruchirappalli, India)and Sheeba J. Priyadarshini (St. Aloysius College and Post Graduate Studies Centre, Bangalore, India)
Copyright: 2021
Pages: 30
Source title:
Machine Learning Approaches for Improvising Modern Learning Systems
Source Author(s)/Editor(s): Zameer Gulzar (BSAR Crescent Institute of Science and Technology, India)and A. Anny Leema (Vellore Institute of Technology (VIT), Vellore, India)
DOI: 10.4018/978-1-7998-5009-0.ch011
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Abstract
Ontologies are the entities that are built to gather knowledge from the chosen domain and make it available to both machines and humans. In this chapter, an ontology that structures all the processes involved in the metallurgical extraction of the metals has been modelled. Ontology Development 101 methodology with minor modifications has been adopted to model the ontologies for metallurgy as the principal domain, and the processes involved in the various fields of metallurgy have been modelled into an ontology by defining the classes and the relationship between them. The model is implemented using Protégé and quantitatively evaluated using the semiotics approach. To comprehensively demonstrate the applicability of the developed ontology, an algorithm for retrieval of entities from the web incorporating particle swarm optimization and that makes use of the modelled ontology has been proposed. Finally, the quality of the modelled ontology and as well as the performance efficiency of the entity retrieval has been quantitatively evaluated.
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