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» Data Mining: Machine Learning, Statistics, and Databases
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ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 6 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 7 days ago
Camouflaged fraud detection in domains with complex relationships
We describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. Examples include accounti...
Sankar Virdhagriswaran, Gordon Dakin
CIKM
2009
Springer
15 years 6 months ago
Joint sentiment/topic model for sentiment analysis
Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes ...
Chenghua Lin, Yulan He
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 7 days ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
15 years 9 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...