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» A Genetic Algorithm for Clustering on Very Large Data Sets
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GECCO
2003
Springer
141views Optimization» more  GECCO 2003»
14 years 1 months ago
Finding the Optimal Gene Order in Displaying Microarray Data
The rapid advances of genome-scale sequencing have brought out the necessity of developing new data processing techniques for enormous genomic data. Microarrays, for example, can g...
Seung-Kyu Lee, Yong-Hyuk Kim, Byung Ro Moon
ASUNAM
2010
IEEE
13 years 7 months ago
A Multiobjective and Evolutionary Clustering Method for Dynamic Networks
—The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. Previous evolutionary based clustering methods try to maxi...
Francesco Folino, Clara Pizzuti
AUSAI
2003
Springer
14 years 1 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
BMCBI
2008
119views more  BMCBI 2008»
13 years 8 months ago
A new method for 2D gel spot alignment: application to the analysis of large sample sets in clinical proteomics
Background: In current comparative proteomics studies, the large number of images generated by 2D gels is currently compared using spot matching algorithms. Unfortunately, differe...
Sabine Pérès, Laurence Molina, Nicol...
CEC
2009
IEEE
14 years 1 months ago
Distributed genetic algorithm using automated adaptive migration
—We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algori...
Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim