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CIKM
2006
Springer
13 years 8 months ago
Finding highly correlated pairs efficiently with powerful pruning
We consider the problem of finding highly correlated pairs in a large data set. That is, given a threshold not too small, we wish to report all the pairs of items (or binary attri...
Jian Zhang, Joan Feigenbaum
KDD
2004
ACM
134views Data Mining» more  KDD 2004»
14 years 5 months ago
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pair
Given a user-specified minimum correlation threshold and a market basket database with N items and T transactions, an all-strong-pairs correlation query finds all item pairs with...
Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Ku...
ICDM
2009
IEEE
181views Data Mining» more  ICDM 2009»
13 years 2 months ago
Efficient Discovery of Frequent Correlated Subgraph Pairs
The recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. In view of this, many graph mining ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
PVLDB
2008
82views more  PVLDB 2008»
13 years 4 months ago
Mining non-redundant high order correlations in binary data
Many approaches have been proposed to find correlations in binary data. Usually, these methods focus on pair-wise correlations. In biology applications, it is important to find co...
Xiang Zhang, Feng Pan, Wei Wang 0010, Andrew B. No...
JMLR
2010
117views more  JMLR 2010»
12 years 11 months ago
Exploiting the High Predictive Power of Multi-class Subgroups
Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. A number of multi-class subgroup disc...
Tarek Abudawood, Peter A. Flach