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KDD
2001
ACM
163views Data Mining» more  KDD 2001»
14 years 5 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn
SDM
2007
SIAM
140views Data Mining» more  SDM 2007»
13 years 6 months ago
A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions
In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but...
Jing Gao, Wei Fan, Jiawei Han, Philip S. Yu
HPDC
2006
IEEE
13 years 11 months ago
Troubleshooting Distributed Systems via Data Mining
Through massive parallelism, distributed systems enable the multiplication of productivity. Unfortunately, increasing the scale of available machines to users will also multiply d...
David A. Cieslak, Douglas Thain, Nitesh V. Chawla
EDBT
2004
ACM
94views Database» more  EDBT 2004»
14 years 5 months ago
Mining Extremely Skewed Trading Anomalies
Trading surveillance systems screen and detect anomalous trades of equity, bonds, mortgage certificates among others. This is to satisfy federal trading regulations as well as to p...
Wei Fan, Philip S. Yu, Haixun Wang
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 5 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...