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KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 6 months ago
Camouflaged fraud detection in domains with complex relationships
We describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. Examples include accounti...
Sankar Virdhagriswaran, Gordon Dakin
KDD
2005
ACM
137views Data Mining» more  KDD 2005»
16 years 6 months ago
A generalized framework for mining spatio-temporal patterns in scientific data
In this paper, we present a general framework to discover spatial associations and spatio-temporal episodes for scientific datasets. In contrast to previous work in this area, fea...
Hui Yang, Srinivasan Parthasarathy, Sameep Mehta
KDD
2003
ACM
190views Data Mining» more  KDD 2003»
16 years 6 months ago
Distance-enhanced association rules for gene expression
We introduce a novel data mining technique for the analysis of gene expression. Gene expression is the effective production of the protein that a gene encodes. We focus on the cha...
Aleksandar Icev, Carolina Ruiz, Elizabeth F. Ryder
KDD
2002
ACM
175views Data Mining» more  KDD 2002»
16 years 6 months ago
Mining product reputations on the Web
Knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. It is, however, very costly to collect and a...
Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi,...
KDD
2002
ACM
106views Data Mining» more  KDD 2002»
16 years 6 months ago
Selecting the right interestingness measure for association patterns
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava
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