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AI
2005
Springer
15 years 10 months ago
Comparing Dimension Reduction Techniques for Document Clustering
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
MLDM
2005
Springer
15 years 10 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
GECCO
2003
Springer
322views Optimization» more  GECCO 2003»
15 years 9 months ago
AntClust: Ant Clustering and Web Usage Mining
Abstract. In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuou...
Nicolas Labroche, Nicolas Monmarché, Gilles...
ACL
2003
15 years 6 months ago
Clustering Polysemic Subcategorization Frame Distributions Semantically
Previous research has demonstrated the utility of clustering in inducing semantic verb classes from undisambiguated corpus data. We describe a new approach which involves clusteri...
Anna Korhonen, Yuval Krymolowski, Zvika Marx
CSDA
2010
105views more  CSDA 2010»
15 years 4 months ago
James-Stein shrinkage to improve k-means cluster analysis
We study a general algorithm to improve accuracy in cluster analysis that employs the James-Stein shrinkage effect in k-means clustering. We shrink the centroids of clusters towar...
Jinxin Gao, David B. Hitchcock