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HAIS
2011
Springer
10 years 10 months ago
Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm
A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identiļ¬e...
Stephen G. Matthews, Mario A. Góngora, Adri...
ADMA
2008
Springer
152views Data Mining» more  ADMA 2008»
12 years 1 months ago
MPSQAR: Mining Quantitative Association Rules Preserving Semantics
To avoid the loss of semantic information due to the partition of quantitative values, this paper proposes a novel algorithm, called MPSQAR, to handle the quantitative association ...
Chunqiu Zeng, Jie Zuo, Chuan Li, Kaikuo Xu, Shengq...
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