Integration of Cluster Analysis and Ant Colony System in Association Rule Mining

• Main Authors: Szu-Yu lin, 林思宇
• Other Authors: Ren-Jieh Kuo
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/s6hs52

碩士 === 國立臺北科技大學 === 工業工程與管理系所 === 93 === In addition to sharing and applying the knowledge in the community, knowledge discovery has become an important issue in the knowledge economic era. Data mining plays an important role of knowledge discovery. Therefore, this study intends to propose a new framework of data mining that does clustering analysis first, and then followed by association rule mining. The study reduced the data dimensions by the classifications of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) first, and then clustered the data set with Self-organizing Map(SOM) network. Finally, we mined the association rule in all clusters by ACS-based association rule mining system. The result showed that the new mining framework can provide not only the better effect, but also the easier way to find the useful rules that maybe hidden in the very large data. In other words, it is easier to extract the useful knowledge by the proposed framework.