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» Mining Very Large Databases
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147
Voted
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 4 months ago
A visual-analytic toolkit for dynamic interaction graphs
In this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, WWW and biological appli...
Xintian Yang, Sitaram Asur, Srinivasan Parthasarat...
127
Voted
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 4 months ago
Mobile call graphs: beyond power-law and lognormal distributions
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Mukund Seshadri, Sridhar Machiraju, Ashwin Sridhar...
131
Voted
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 4 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
133
Voted
KDD
2004
ACM
143views Data Mining» more  KDD 2004»
16 years 4 months ago
Incremental maintenance of quotient cube for median
Data cube pre-computation is an important concept for supporting OLAP(Online Analytical Processing) and has been studied extensively. It is often not feasible to compute a complet...
Cuiping Li, Gao Cong, Anthony K. H. Tung, Shan Wan...
150
Voted
IJCNN
2008
IEEE
15 years 10 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...