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» On Weighting Clustering
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PR
2002
134views more  PR 2002»
14 years 11 months ago
Interactive clustering and merging with a new fuzzy expected value
7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
Carl G. Looney
DCOSS
2005
Springer
15 years 5 months ago
Distributed Energy-Efficient Hierarchical Clustering for Wireless Sensor Networks
Abstract: Since nodes in a sensor network have limited energy, prolonging the network lifetime and improving scalability become important. In this paper, we propose a distributed w...
Ping Ding, JoAnne Holliday, Aslihan Celik
RIAO
2007
15 years 1 months ago
Query Refinement based on Topical Term Clustering
We propose a method for supporting query refinement using topical term clusters. First, we propose a new term weighting method that can extract terms strongly related to a specifi...
Hiromi Wakaki, Tomonari Masada, Atsuhiro Takasu, J...
KBS
2006
150views more  KBS 2006»
14 years 11 months ago
Clusterer ensemble
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Zhi-Hua Zhou, Wei Tang
BMCBI
2008
117views more  BMCBI 2008»
14 years 11 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...