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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 6 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 6 months 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
16 years 3 days 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...
GD
2005
Springer
15 years 11 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 11 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