Integration of rule based and case based reasoning system to support decision making

Abstract

Augmented by rule based reasoning and data mining method, case-based reasoning (CBR) has emerged as a major research area because CBR is not only a psychological theory for human knowledge, but also will be a new comer stone of the intelligent computer system technology. This paper focuses on the coalition between the research areas of Data Mining, CBR System and decision support systems (DSSs). A conceptual framework model for DSSs based on Data mining and CBR is elaborated here. The model consists of a knowledge base, case base reasoning and data mining subsystems. For our research we chose knowledge driven model because the model has capacity to self-learn, identify association between data, classifying and clustering of the data based on the characteristics, suggest recommended actions to users, all these factors incorporate intelligence into the system thus increasing the capacity of problem solving and improve suggestion accuracy.