ABSTRACT
Researchers in agricultural research centers across India work on various aspects of production of major crops. As outcomes of these researches, automated systems and research documents are generated. To have integration of such systems and sharing and reuse of generated knowledge, it must be represented in interoperable format.
With increased use of ontologies, maintenance and evolution of ontologies becomes important. Understanding of domain by experts improves with time, so experts need to incorporate those changes in existing ontology. New information is captured and accommodated in ontology evolution process. Ontology versioning, integration, merging and maintenance are parts of ontology change management. With accommodation of changes in ontology, preserving consistency is also important. Manual matching and evolution of ontologies can be time consuming, complex and error prone. Using decision tree algorithm C4.5, one can find important rules about ontology evolution from knowledge base. The objective of this work is to demonstrate application of decision tree to dataset tuples and find out the knowledge to be extended or changes to be done in nutrition management ontology.
