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Proceedings Paper

The study on genetic algorithm on mining quantitative association rules
Author(s): Yue Wang; Liang Li
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Paper Abstract

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.

Paper Details

Date Published: 2 May 2006
PDF: 7 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 604225 (2 May 2006); doi: 10.1117/12.664644
Show Author Affiliations
Yue Wang, Chongqing Institute of Technology (China)
Liang Li, Chongqing Institute of Technology (China)

Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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