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104
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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 1 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
BMCBI
2005
73views more  BMCBI 2005»
15 years 17 days ago
Evaluation of Glycine max mRNA clusters
Background: Clustering the ESTs from a large dataset representing a single species is a convenient starting point for a number of investigations into gene discovery, genome evolut...
Ronald L. Frank, Fikret Erçal
GLOBECOM
2006
IEEE
15 years 6 months ago
Toposemantic Network Clustering
— We study the problem of building an optimal network-layer clustering hierarchy, where the optimality can be defined using three potentially conflicting metrics: state, delay ...
Leonid B. Poutievski, Kenneth L. Calvert, Jim Grif...
98
Voted
GD
2005
Springer
15 years 6 months ago
Drawing Clustered Graphs in Three Dimensions
Clustered graph is a very useful model for drawing large and complex networks. This paper presents a new method for drawing clustered graphs in three dimensions. The method uses a ...
Joshua Wing Kei Ho, Seok-Hee Hong
ICCSA
2005
Springer
15 years 6 months ago
A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering
In this paper, we propose a new clustering procedure for high dimensional microarray data. Major difficulty in cluster analysis of microarray data is that the number of samples to ...
Ryo Yoshida, Seiya Imoto, Tomoyuki Higuchi