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

摘要：

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.

关键词： Knowledge acquisition Bayesian network Rough set theory

作者: Chih-Cheng Chen Ming-Lang Tseng Wei-Ting Hsu

作者单位: Department of Finance, MingDao University, Taiwan Department of Business Innovation and Development, MingDao University, Taiwan

会议类型: 国际会议

会议名称: The Third International Conference on Operations and Supply Chain Management(第三届运营与供应链管理国际会议)

会议地点: 武汉

会议语种:英文

页码: 994-1000

在线出版日期: 2009-07-28（万方平台首次上网日期，不代表论文的发表时间）