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» An objective evaluation criterion for clustering
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FLAIRS
2001
13 years 9 months ago
A Lattice-Based Approach to Hierarchical Clustering
The paper presents an approach to hierarchical clustering based on the use of a least general generalization (lgg) operator to induce a lattice structure of clusters and a categor...
Zdravko Markov
SSDBM
2005
IEEE
159views Database» more  SSDBM 2005»
14 years 1 months ago
Clustering Moving Objects via Medoid Clusterings
Modern geographic information systems do not only have to handle static information but also dynamically moving objects. Clustering algorithms for these moving objects provide new...
Hans-Peter Kriegel, Martin Pfeifle
TSD
2009
Springer
14 years 7 days ago
Objective vs. Subjective Evaluation of Speakers with and without Complete Dentures
Abstract. For dento-oral rehabilitation of edentulous (toothless) patients, speech intelligibility is an important criterion. 28 persons read a standardized text once with and once...
Tino Haderlein, Tobias Bocklet, Andreas Maier, Elm...
KDD
1995
ACM
98views Data Mining» more  KDD 1995»
13 years 11 months ago
Optimization and Simplification of Hierarchical Clusterings
Clustering is often used to discover structure in data. Clustering systems differ in the objective function used to evaluate clustering quality and the control strategy used to se...
Douglas Fisher
PRL
2006
139views more  PRL 2006»
13 years 7 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...