Development of a Method for Ontology-Based Empirical Knowledge Representation and Reasoning

• Main Authors: Ting-chien Wu, 吳定謙
• Other Authors: Yuh-Min Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/43788445466159876902

碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 97 === With the advent of knowledge economy, knowledge has become the most important asset of enterprises in the 21st century. There are also two types of knowledge: tacit and explicit. Tacit knowledge is personal knowledge that is often difficult to articulate and communicate. It has been characterized as being unarticulated and context specific. As compared to explicit knowledge, tacit knowledge is difficult to codify. But, articulating tacit knowledge is important for any organization so it does not lose that knowledge if the individual who owns it leaves the organization. A empirical knowledge is a kind of tacit knowledge, which is the knowledge or understanding by experience. However, empirical knowledge is ill-structured, and therefore difficult to formalize. Since empirical knowledge is not easily represented or stored, empirical knowledge sharing is ineffective. Some examples of empirical knowledge include heuristics, skills, and special know-how. The objective of this research is to develop a method to convert empirical knowledge into formatted representation, assist knowledge demanders to efficiently and accurately understand the useful meaning from empirical knowledge, to facilitate empirical knowledge sharing and reusing by ontology reasoning rule, and help problem-solving and decision-making in the future. The objective can be achieved through (1) design of a model for Ontology-Based Multi-Layers empirical knowledge representation, (2) develop of OWL-Based empirical knowledge ontology, (3) develop of a method for Ontology-Based Single-Layers empirical knowledge reasoning, and (4) develop of a method for Ontology-Based Cross-Layers empirical knowledge reasoning.