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» An objective evaluation criterion for clustering
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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 9 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2002
ACM
170views Data Mining» more  KDD 2002»
14 years 9 months ago
Enhanced word clustering for hierarchical text classification
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
OODBS
2000
110views Database» more  OODBS 2000»
14 years 16 days ago
Opportunistic Prioritised Clustering Framework (OPCF)
Ever since the `early days' of database management systems, clustering has proven to be one of the most effective performance enhancement techniques for object oriented datab...
Zhen He, Alonso Marquez, Stephen Blackburn
MMM
2010
Springer
157views Multimedia» more  MMM 2010»
14 years 5 months ago
A Novel Trajectory Clustering Approach for Motion Segmentation
We propose a novel clustering scheme for spatio-temporal segmentation of sparse motion fields obtained from feature tracking. The approach allows for the segmentation of meaningfu...
Matthias Zeppelzauer, Maia Zaharieva, Dalibor Mitr...
ICPR
2002
IEEE
14 years 10 months ago
Prototype Selection for Finding Efficient Representations of Dissimilarity Data
The nearest neighbor (NN) rule is a simple and intuitive method for solving classification problems. Originally, it uses distances to the complete training set. It performs well, ...
Elzbieta Pekalska, Robert P. W. Duin