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» Techniques of Cluster Algorithms in Data Mining
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DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
15 years 10 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu
TKDE
2008
127views more  TKDE 2008»
15 years 6 months ago
Maximal Subspace Coregulated Gene Clustering
Clustering is a popular technique for analyzing microarray data sets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify coregu...
Yuhai Zhao, Jeffrey Xu Yu, Guoren Wang, Lei Chen 0...
DKE
2010
167views more  DKE 2010»
15 years 3 months ago
Discovering private trajectories using background information
Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traf...
Emre Kaplan, Thomas Brochmann Pedersen, Erkay Sava...
PAKDD
2009
ACM
103views Data Mining» more  PAKDD 2009»
16 years 1 months ago
Hot Item Detection in Uncertain Data
Abstract. An object o of a database D is called a hot item, if there is a sufficiently large population of other objects in D that are similar to o. In other words, hot items are ...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
ISPA
2005
Springer
16 years 1 days ago
COMPACT: A Comparative Package for Clustering Assessment
Abstract. There exist numerous algorithms that cluster data-points from largescale genomic experiments such as sequencing, gene-expression and proteomics. Such algorithms may emplo...
Roy Varshavsky, Michal Linial, David Horn