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ICANN
2009
Springer
15 years 2 months ago
A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...
INCDM
2010
Springer
208views Data Mining» more  INCDM 2010»
14 years 11 months ago
Combining Unsupervised and Supervised Data Mining Techniques for Conducting Customer Portfolio Analysis
Abstract. Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies i...
Zhiyuan Yao, Annika H. Holmbom, Tomas Eklund, Barb...
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
15 years 2 months ago
Hybridizing evolutionary algorithms and clustering algorithms to find source-code clones
This paper presents a hybrid approach to detect source-code clones that combines evolutionary algorithms and clustering. A case-study is conducted on a small C++ code base. The pr...
Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maleti...
INDIASE
2009
ACM
15 years 3 months ago
Computing dynamic clusters
When trying to reverse engineer software, execution trace analysis is increasingly used. Though, by using this technique we are quickly faced with an enormous amount of data that ...
Philippe Dugerdil, Sebastien Jossi
IJIT
2004
14 years 10 months ago
IMDC: An Image-Mapped Data Clustering Technique for Large Datasets
In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthe...
Faruq A. Al-Omari, Nabeel I. Al-Fayoumi