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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
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
155
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KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 4 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik
181
Voted
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
16 years 4 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
128
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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