A Promising Method of Knowledge Acquisition Using a Combination of Bayesian Network and Rough Set Theory

The determinant of survival in the knowledge-based economy is knowledge development and management, which usually starts with knowledge acquisition followed by knowledge organization and utilization. Although several studies demonstrate that data mining techniques and the rough sets theory (RST) are useful to knowledge acquisition, few people really enjoy or benefit from them in daily work and life. This is primarily because we lack a practical way of implementing them, a method which can reliably provide us with certain results in knowledge acquisition. This paper proposes a knowledge acquisition process that enables us to gain knowledge useful for decision support through a combination of Bayesian networks and the RST. An empirical study is presented to illustrate the application of the proposed method. According to the findings of this study, management implications and conclusions are discussed.