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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 4 months ago
Relational data pre-processing techniques for improved securities fraud detection
Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarel...
Andrew Fast, Lisa Friedland, Marc Maier, Brian Tay...
143
Voted
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 4 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 4 months ago
Detecting outliers using transduction and statistical testing
Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, ...
Daniel Barbará, Carlotta Domeniconi, James ...
134
Voted
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 4 months ago
High-throughput Protein Interactome Data: Minable or Not?
There is an emerging trend in post-genome biology to study the collection of thousands of protein interaction pairs (protein interactome) derived from high-throughput experiments....
Jake Yue Chen, Andrey Y. Sivachenko, Lang Li
126
Voted
KDD
2002
ACM
183views Data Mining» more  KDD 2002»
16 years 4 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
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