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Fourth IEEE International Conference on Data Mining (ICDM'04)
Integrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining
Brighton, United Kingdom
November 01-November 04
ISBN: 0-7695-2142-8
ASCII Text
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Mehmet Kaya, Reda Alhajj, "Integrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining," Data Mining, IEEE International Conference on, pp. 431-434, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004.
 
 
BibTex
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@article{ 10.1109/ICDM.2004.10050,
author = {Mehmet Kaya and Reda Alhajj},
title = {Integrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2004},
isbn = {0-7695-2142-8},
pages = {431-434},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10050},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Mining, IEEE International Conference on
TI - Integrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining
SN - 0-7695-2142-8
SP431
EP434
A1 - Mehmet Kaya,
A1 - Reda Alhajj,
PY - 2004
KW - null
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
Mehmet Kaya, Firat University, Turkey
Reda Alhajj, University of Calgary, Canada
In this paper, we propose an automated method to decide on the number of fuzzy sets and for the autonomous mining of both fuzzy sets and fuzzy association rules. We compare the proposed multi-objective GA based approach with: 1) CURE based approach; 2) Chien et al clustering approach. Experimental results on 100K transactions extracted from the adult data of United States census in year 2000 show that the proposed method exhibits good performance over the other two approaches in terms of runtime, number of large itemsets and number of association rules.
Citation:
Mehmet Kaya, Reda Alhajj, "Integrating Multi-Objective Genetic Algorithms into Clustering for Fuzzy Association Rules Mining," icdm, pp.431-434, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004
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