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CORR
2012
Springer
202views Education» more  CORR 2012»
12 years 3 months ago
Mining Flipping Correlations from Large Datasets with Taxonomies
In this paper we introduce a new type of pattern – a flipping correlation pattern. The flipping patterns are obtained from contrasting the correlations between items at diffe...
Marina Barsky, Sangkyum Kim, Tim Weninger, Jiawei ...
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,...
PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
FEGC
2008
104views Biometrics» more  FEGC 2008»
13 years 9 months ago
Mining Implications from Lattices of Closed Trees
We propose a way of extracting high-confidence association rules from datasets consisting of unlabeled trees. The antecedents are obtained through a computation akin to a hypergrap...
José L. Balcázar, Albert Bifet, Anto...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 8 months ago
Efficient closed pattern mining in the presence of tough block constraints
In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbase...
Krishna Gade, Jianyong Wang, George Karypis