Authors: Archana Chougule; Vijay Kumar Jha; Debajyoti Mukhopadhyay
Addresses: Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India ' Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India ' Adamas University, Adamas Knowledge City, Kolkata – 700 126, West Bengal, India
Abstract: For any decision support system, having meaningful, up-to-date, interoperable and consistent knowledge base is important. Ontologies can be used for representing knowledge semantics and knowledge sharing. Hence ontologies are getting more importance these days as heterogeneous integrated systems are used in almost all areas. Ontology gets evolved with increase in domain knowledge of experts. Change management of ontology is must to keep consistency of knowledge base. This paper demonstrates use of decision tree for ontology building and evolution. Detail algorithm for extending ontology from decision tree is discussed in the paper. For decision support using knowledge stored in ontology, ontology reasoning is used. Semantic web rule language is the technique used for ontology reasoning. Accuracy of decision support depends on strength and correctness of inference logic. Paper describes how accuracy of decision support improves with semi-automated construction of SWRL rules. The approach is validated with example of nutrition management system for grapes.
Keywords: decision support; ontology evolution; decision tree; semantic web rule language; SWRL; grapes; nutrition management.
International Journal of Information and Decision Sciences, 2019 Vol.11 No.3, pp.234 - 255
Received: 24 Apr 2017
Accepted: 27 Jan 2018
Published online: 29 Aug 2019 *