doi: 10.4304/jsw.6.1.91-99
ECOGA: Efficient Data Mining Approach for Fuzzy Association Rules
- 1 State key lab of software engineering, Wuhan University Wuhan 430072, China
- 2 College of Computer Science, South-Central University for Nationalities Wuhan 430074, China
- 3 Computer School, Wuhan University, Wuhan, 430072, China
Abstract
Data mining is concerned with developing algorithms and computational tools and techniques to help people extract patterns from data. In this paper an efficient data mining approach, which is based on fuzzy set theory and clonal selection algorithm, is proposed. The main motivation is to benefit from the global search performed by this kind of algorithms. Experimental results show the number of fuzzy association rules obtained with the proposed method is larger than those obtained by applying other methods.
Keywords
- data mining
- association rules
- fuzzy se
How to Cite
Wanneng Shu and Lixin Ding, "ECOGA: Efficient Data Mining Approach for Fuzzy Association Rules," Journal of Software, vol. 6, no. 1, pp. 91-99, 2011. https://doi.org/ 10.4304/jsw.6.1.91-99
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).