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» Discovering Frequent Closed Itemsets for Association Rules
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APWEB
2005
Springer
14 years 1 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...
SIGMOD
1997
ACM
148views Database» more  SIGMOD 1997»
13 years 12 months ago
Beyond Market Baskets: Generalizing Association Rules to Correlations
One of the most well-studied problems in data mining is mining for association rules in market basket data. Association rules, whose significance is measured via support and confi...
Sergey Brin, Rajeev Motwani, Craig Silverstein
HAIS
2011
Springer
12 years 11 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...
KDD
1997
ACM
104views Data Mining» more  KDD 1997»
13 years 11 months ago
An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
Efficient discover of association rules in large databases is a we 1 studied problem and several ap-1y proaches have been proposed. However, it is non trivial to maintain the asso...
Shiby Thomas, Sreenath Bodagala, Khaled Alsabti, S...
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 9 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin