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» Association rules mining using heavy itemsets
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HAIS
2011
Springer
14 years 1 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 identifie...
Stephen G. Matthews, Mario A. Góngora, Adri...
69
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JIS
2007
95views more  JIS 2007»
14 years 9 months ago
Combined association rules for dealing with missing values
With the rapid increase in the use of databases, the problem of missing values inevitably arises. The techniques developed to effectively recover these missing values should be hi...
Jau-Ji Shen, Chin-Chen Chang, Yu-Chiang Li
FIMI
2004
175views Data Mining» more  FIMI 2004»
14 years 11 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan
DEXA
2004
Springer
153views Database» more  DEXA 2004»
15 years 3 months ago
A New Approach of Eliminating Redundant Association Rules
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant ...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
15 years 10 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald