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» On Weighting Clustering
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PVLDB
2008
107views more  PVLDB 2008»
13 years 4 months ago
Constrained locally weighted clustering
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Hao Cheng, Kien A. Hua, Khanh Vu
IJAR
2008
88views more  IJAR 2008»
13 years 5 months ago
Clustering decomposed belief functions using generalized weights of conflict
We develop a method for clustering all types of belief functions, in particular non-consonant belief functions. Such clustering is done when the belief functions concern multiple ...
Johan Schubert
BMCBI
2008
142views more  BMCBI 2008»
13 years 6 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
CIT
2004
Springer
13 years 11 months ago
Associativity Based Mobility-Adaptive K-Clustering in Mobile Ad-Hoc Networks
To solve the scalability issue of ad hoc network, a new cluster maintenance protocol is proposed. Clusters may change dynamically, reflecting the mobility of the underlying networ...
Chinnappan Jayakumar, Chenniappan Chellappan
COCOA
2008
Springer
13 years 7 months ago
Going Weighted: Parameterized Algorithms for Cluster Editing
The goal of the Cluster Editing problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union of cliques. This problem i...
Sebastian Böcker, Sebastian Briesemeister, Qu...