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» Numbers in Multi-relational Data Mining
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KDD
2004
ACM
112views Data Mining» more  KDD 2004»
16 years 5 months ago
A rank sum test method for informative gene discovery
Finding informative genes from microarray data is an important research problem in bioinformatics research and applications. Most of the existing methods rank features according t...
Lin Deng, Jian Pei, Jinwen Ma, Dik Lun Lee
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
16 years 5 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
KDD
2007
ACM
220views Data Mining» more  KDD 2007»
16 years 5 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
KDD
2005
ACM
168views Data Mining» more  KDD 2005»
16 years 5 months ago
Nomograms for visualizing support vector machines
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
16 years 5 months ago
Cluster-based concept invention for statistical relational learning
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Alexandrin Popescul, Lyle H. Ungar