The study on genetic algorithm on mining quantitative association rules - art. no. 604225

被引:1
|
作者
Wang, Y [1 ]
Li, L [1 ]
机构
[1] Chongqing Inst Technol, Dept Comp Sci & Engn, Chongqing 400050, Peoples R China
来源
ICMIT 2005: Control Systems and Robotics, Pts 1 and 2 | 2005年 / 6042卷
关键词
gene algorithm; association rules; KDD; fuzzy clustering;
D O I
10.1117/12.664644
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the development of the internet and the application of databases, seas of storage of data have become available. How to use the data for humans is the task of data mining. But in the process of data mining, a problem often encountered is that mining association rules on the quantitative attributes in RDBMS (Relational Database Management System) or Web logs. A genetic algorithm is proposed in the present paper to solve the clustering problem which can be solved by FCM (Fuzzy Clustering Method), so as to avoid the local optimization that often occurs in FCM. The quantitative attributes can be converted into categorical attributes and then the categorical attributes are mapped into Boolean attributes, so that many association algorithms can be used to mine significant association rules.
引用
收藏
页码:4225 / 4225
页数:7
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