ABSTRACT
Ontology can be developed from scratch by defining all terms explicitly, or it can be generated by extracting text from relevant documents. Clustering-based or classification-based approaches are used for ontology building. Clustering-based approaches use semantic distance between terms and merge similar terms to create clusters. Python script is used to generate ontology from weather observations based on SSN ontology. Special notations for ontology merging called Ontology Merging notations are presented by Alma Delia Cuevas Rasgado and Arenas. They also presented ontology merging algorithm where merging takes place automatically without user intervention. Fully automated ontology matching using upper ontologies is proposed by Viviana Mascardi et al. Three algorithms, namely uo-match, structural-uo-match and mixed-match are implemented for ontology matching. A decision support system for management of Powdery Mildew in grapes is developed by K. Y. Mundankar et al. They estimate disease risk by considering plant growth stage and weather conditions.
