An Ontology Evolution System based on Belief Change Theory and Genetic Programming

• Main Authors: Wan-Chen Hou, 侯宛辰
• Other Authors: Deng-Neng Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/29500874976321379721

碩士 === 國立屏東科技大學 === 資訊管理系所 === 97 === Ontology is one of the most important content theories in artificial intelligence (AI) applications. It can be used to represent complex knowledge in a condensed and structural way, including the basic categories of beings and their relations. Ontology has been wildly applied in knowledge representation in computer science, and lots of applications are designed based on ontology technologies. While ontology is using for encoding human knowledge, with the variation characteristics of knowledge, how to modify ontology to fit to knowledge change is a critical problem. The ontology should adapt to knowledge variation to maintain utility, efficacy and reliability. In this research, we proposed an ontology evolution algorithm (OEA) which is based on belief change and genetic programming. We also implemented an ontology evolution system to examine the accuracy of evolved results. The results show that our ontology evolution system could partially help ontology engineers to construct ontology.