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JDWM
2006
84views more  JDWM 2006»
15 years 6 months ago
Discovering Surprising Instances of Simpson's Paradox in Hierarchical Multidimensional Data
This paper focuses on the discovery of surprising, unexpected patterns, based on a data mining method that consists of detecting instances of Simpson's paradox. By its very n...
Carem C. Fabris, Alex Alves Freitas
DKE
2008
124views more  DKE 2008»
15 years 6 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios
SIGMOD
2010
ACM
196views Database» more  SIGMOD 2010»
15 years 7 months ago
GAIA: graph classification using evolutionary computation
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Ning Jin, Calvin Young, Wei Wang
TKDE
2008
136views more  TKDE 2008»
15 years 6 months ago
Efficient Correlation Search from Graph Databases
Correlation mining has gained great success in many application domains for its ability to capture underlying dependencies between objects. However, research on correlation mining ...
Yiping Ke, James Cheng, Wilfred Ng
KDD
2003
ACM
145views Data Mining» more  KDD 2003»
16 years 7 months ago
Carpenter: finding closed patterns in long biological datasets
The growth of bioinformatics has resulted in datasets with new characteristics. These datasets typically contain a large number of columns and a small number of rows. For example,...
Feng Pan, Gao Cong, Anthony K. H. Tung, Jiong Yang...