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Decision support for nutrition management of grapes using ontology based on decision trees

Author

Listed:
  • Archana Chougule
  • Vijay Kumar Jha
  • Debajyoti Mukhopadhyay

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.

Suggested Citation

  • Archana Chougule & Vijay Kumar Jha & Debajyoti Mukhopadhyay, 2019. "Decision support for nutrition management of grapes using ontology based on decision trees," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 11(3), pages 234-255.
    • Handle: RePEc:ids:ijidsc:v:11:y:2019:i:3:p:234-255
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