An Ontology-based Knowledge Mining Model for Effective Exploitation of Agro Information

Abstract

The quality of agriculture depends on the quality of the yield, which is usually obtained through the well-being of the crop. The quality of any crop depends on the minerals in the soil, the type of soil, the location, and the seasons. The crop yield depends on soil fertility, availability of water, climate, and disease prevention. Although this information is prevailing in plenty among the expert farmers, the means of abducting the information to the future generation has not been much promoted. Hence, the knowledge disseminated regarding agriculture becomes scarce, affecting the entire agricultural process. Given these facts, a single source, strong knowledge management system is proposed to be designed. The system aims to embrace the different kinds of knowledge associated with agriculture and attempt to obtain a single source of agro information that is very much usable and reusable to the users. To ensure the maximum level of reusability, the knowledge of the domain needs to be modeled and represented in a way that is scalable and flexible. One of the knowledge representation techniques that emphasizes on reusability and scalability is ontology. Thus, this paper attempts to design an ontology-based agro knowledge management system. A rule base is constructed to improve the expressiveness of the knowledge. An incremental mining approach is adopted to extract the knowledge from multiple ontology. To understand better to aid decision-making, a visualization task is carried out. A multi ontology-based knowledge mining model is attempted in this research to provide better insight regarding agro knowledge.

Keywords:

• Crop ontology
• Incremental mining approach
• Location ontology
• Season ontology
• Soil ontology
• Ontology visualization

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

E. Murali

E Murali is a research scholar in the Vellore Institute of Technology , Vellore, India. He received the bachelor’s degree in computer science and engineering from Anna University affiliated college and master’s in computer science and engineering from Dr MGR Research and Educational Institute. His areas of interest include data mining, ontology mining and knowledge engineering. Email: [email protected]

S. Margret Anouncia

S Margret Anouncia is professor at the Vellore Institute of Technology, Vellore, India. She received her bachelor’s degree in computer science and engineering from Bharathidasan University and master’s in software engineering from Anna University. She has been awarded a doctorate in computer science and engineering at VIT University. Her area of specialization includes digital image processing, software engineering, and knowledge engineering.