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» Mining Association Rules between Sets of Items in Large Data...
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DATAMINE
2007
101views more  DATAMINE 2007»
14 years 9 months ago
Using metarules to organize and group discovered association rules
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
Abdelaziz Berrado, George C. Runger
SIGMOD
2004
ACM
196views Database» more  SIGMOD 2004»
15 years 9 months ago
FARMER: Finding Interesting Rule Groups in Microarray Datasets
Microarray datasets typically contain large number of columns but small number of rows. Association rules have been proved to be useful in analyzing such datasets. However, most e...
Gao Cong, Anthony K. H. Tung, Xin Xu, Feng Pan, Ji...
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APPINF
2003
14 years 11 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
VLDB
1998
ACM
147views Database» more  VLDB 1998»
15 years 1 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
KAIS
2008
119views more  KAIS 2008»
14 years 9 months ago
An information-theoretic approach to quantitative association rule mining
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Yiping Ke, James Cheng, Wilfred Ng