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ICML
2007
IEEE
14 years 6 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
13 years 7 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»
12 years 1 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»
11 years 8 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»
13 years 5 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...