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» On the Comparability of Software Clustering Algorithms
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GECCO
2003
Springer
182views Optimization» more  GECCO 2003»
14 years 29 days ago
Modeling the Search Landscape of Metaheuristic Software Clustering Algorithms
Abstract. Software clustering techniques are useful for extracting architectural information about a system directly from its source code structure. This paper starts by examining ...
Brian S. Mitchell, Spiros Mancoridis
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 8 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
AI
2005
Springer
14 years 1 months ago
Comparing Dimension Reduction Techniques for Document Clustering
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
HIPC
2009
Springer
13 years 5 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
GECCO
2005
Springer
146views Optimization» more  GECCO 2005»
14 years 1 months ago
An empirical study of the robustness of two module clustering fitness functions
Two of the attractions of search-based software engineering (SBSE) derive from the nature of the fitness functions used to guide the search. These have proved to be highly robust...
Mark Harman, Stephen Swift, Kiarash Mahdavi