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» A new clustering algorithm for coordinate-free data
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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
14 years 29 days ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 1 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
IDA
2003
Springer
14 years 1 months ago
Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points
This paper proposes a new clustering algorithm in the fuzzy-c-means family, which is designed to cluster time series and is particularly suited for short time series and those wit...
Carla S. Möller-Levet, Frank Klawonn, Kwang-H...
PAKDD
2009
ACM
225views Data Mining» more  PAKDD 2009»
14 years 5 months ago
Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...
GECCO
2003
Springer
322views Optimization» more  GECCO 2003»
14 years 1 months ago
AntClust: Ant Clustering and Web Usage Mining
Abstract. In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuou...
Nicolas Labroche, Nicolas Monmarché, Gilles...