Knowledge Engineering For An Expert System On Crop Disease Management

Expert system is the computer system that solves a domain specific real-world problem using human knowledge and reasoning expertise. Knowledge and inference are the two important parts of an ES. In the development of disease diagnostic ES, knowledge engineering and its maintenance is a big challenge as knowledge involved is of dynamic nature. The classification scheme of concepts of disease symptoms is an important issue in the design of entities or objects dealing with disease knowledge. In this work, the complete process of knowledge acquisition and engineering for disease management of crops has been standardized and a new prototype of web-based knowledge management system (KMS) has been developed. The different components of KMS include efficient tools for knowledge acquisition, storing, knowledge engineering, processing of knowledge, management of knowledge, associated reasoning services and a new interface to define, manipulate and query for disease diagnostic knowledge. The current paper discusses the adopted development Expert system is the computer system that solves a domain specific real-world problem using human knowledge and reasoning expertise. Knowledge and inference are the two important parts of an ES. In the development of disease diagnostic ES, knowledge engineering and its maintenance is a big challenge as knowledge involved is of dynamic nature. The classification scheme of concepts of disease symptoms is an important issue in the design of entities or objects dealing with disease knowledge. In this work, the complete process of knowledge acquisition and engineering for disease management of crops has been standardized and a new prototype of web-based knowledge management system (KMS) has been developed. The different components of KMS include efficient tools for knowledge acquisition, storing, knowledge engineering, processing of knowledge, management of knowledge, associated reasoning services and a new interface to define, manipulate and query for disease diagnostic knowledge. The current paper discusses the adopted development