MINING FUZZY ASSOCIATION RULES FROM THE ASP DATABASE
Association rules have been used as an efficient decision-making strategy in many fields. Along with the increasing competition for customers among many application service providers (ASPs), decision makers of ASPs hope to find useful and potent association rules that will help them track users demands and make correct decisions. The characters of ASP platform itself bespeak that it is a possible way to mine association rules from ASP. Every ASP platform has a self-contained database where vast data are stored and invisible association rules hide. Parallel mining technique among multi-tables is applied in the paper. An experiment of mining fuzzy association rules is given, and GA, a new association rule mining method, has been used in the experiment. The method of treating quantitive attributes values has been narrated in detail. And the results of the experiment show that GA based fuzzy association rules mining method is really of efficiency.
Data mining Association rules Genetic algorithms Knowledge discovery
Wang Bin Xie Qing-sheng
School of Mechanical Engineering, Yancheng Institute of Technology, Yancheng Jiangsu, 224002, China CAD/CIMS Institute, Guizhou University, Guiyang Guizhou, 550003, China
国际会议
5th International Conference on e-Engineering & Digital Enterprise Technology(第5届e工程及数字企业国际学术会议)
贵阳
英文
265-270
2006-08-16（万方平台首次上网日期，不代表论文的发表时间）