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NIPS
2008
15 years 2 months ago
Measures of Clustering Quality: A Working Set of Axioms for Clustering
Aiming towards the development of a general clustering theory, we discuss abstract axiomatization for clustering. In this respect, we follow up on the work of Kleinberg, ([1]) tha...
Shai Ben-David, Margareta Ackerman
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
15 years 10 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
ISPASS
2006
IEEE
15 years 7 months ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder
116
Voted
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
15 years 6 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
MCS
2001
Springer
15 years 5 months ago
Finding Consistent Clusters in Data Partitions
Abstract. Given an arbitrary data set, to which no particular parametrical, statistical or geometrical structure can be assumed, different clustering algorithms will in general pr...
Ana L. N. Fred