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CLASSIFICATION
2010
13 years 7 months ago
Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads
: The issue of determining "the right number of clusters" in K-Means has attracted considerable interest, especially in the recent years. Cluster intermix appears to be a...
Mark Ming-Tso Chiang, Boris Mirkin
DBA
2004
113views Database» more  DBA 2004»
13 years 11 months ago
A Quality Measure for Distributed Clustering
Clustering has become an increasingly important task in modern application domains. Mostly, the data are originally collected at different sites. In order to extract information f...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
SDM
2009
SIAM
215views Data Mining» more  SDM 2009»
14 years 7 months ago
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
ICPR
2008
IEEE
14 years 4 months ago
Unsupervised clustering using hyperclique pattern constraints
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
IJUFKS
2007
108views more  IJUFKS 2007»
13 years 10 months ago
Resampling for Fuzzy Clustering
Abstract. Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the nu...
Christian Borgelt