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PAMI
2002
243views more  PAMI 2002»
13 years 4 months ago
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
13 years 11 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
CORR
2008
Springer
158views Education» more  CORR 2008»
13 years 5 months ago
Improved Smoothed Analysis of the k-Means Method
The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving...
Bodo Manthey, Heiko Röglin
ICONIP
2008
13 years 6 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...
DMIN
2006
122views Data Mining» more  DMIN 2006»
13 years 6 months ago
Clustering of Bi-Dimensional and Heterogeneous Time Series: Application to Social Sciences Data
We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
Rémi Gaudin, Sylvaine Barbier, Nicolas Nico...