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ICML
2007
IEEE
15 years 10 months ago
Best of both: a hybridized centroid-medoid clustering heuristic
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...
Nizar Grira, Michael E. Houle
ICONIP
2008
14 years 11 months ago
Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity
In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kol...
Tina Geweniger, Frank-Michael Schleif, Alexander H...
HICSS
2012
IEEE
268views Biometrics» more  HICSS 2012»
13 years 5 months ago
Goals and Tasks: Two Typologies of Citizen Science Projects
—Citizen science is a form of research collaboration involving members of the public in scientific research projects to address real-world problems. Often organized as a virtual...
Andrea Wiggins, Kevin Crowston
SDM
2012
SIAM
452views Data Mining» more  SDM 2012»
12 years 12 months ago
Density-based Projected Clustering over High Dimensional Data Streams
Clustering of high dimensional data streams is an important problem in many application domains, a prominent example being network monitoring. Several approaches have been lately ...
Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer...
CORR
2010
Springer
219views Education» more  CORR 2010»
14 years 9 months ago
Clustering high dimensional data using subspace and projected clustering algorithms
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdull...