DocumentCode :
2398996
Title :
Achieving Natural Clustering by Validating Results of Iterative Evolutionary Clustering Approach
Author :
Özyer, Tansel ; Alhajj, Reda
Author_Institution :
Dept. of Comput. Sci., Calgary Univ., Alta.
fYear :
2006
fDate :
Sept. 2006
Firstpage :
488
Lastpage :
493
Abstract :
Clustering is an essential process that leads to the classification of a given set of instances based on user-specified criteria; and different factors may lead to different clustering results. Thus, a large number of clustering algorithms exist to satisfy different purposes. However, scalability and the fact that algorithms in general need the number of clusters be specified a priori, which is mostly hard to estimate even for domain experts, are two challenges that motivate the development of new algorithms. This paper presents a novel approach to handle these two issues. We mainly developed a clustering method that works as an iterative approach to handle the scalability problem; and we utilize multi-objective genetic algorithm combined with validity indexes to decide on the number of clusters. The basic idea is to partition the dataset first; then cluster each partition separately. Finally, each obtained cluster is treated as a single instance (represented by its centroid) and a conquer process is performed to get the final clustering of the complete dataset. Test results on one large real dataset demonstrate the applicability and effectiveness of the proposed approach
Keywords :
data analysis; genetic algorithms; iterative methods; pattern classification; pattern clustering; clustering algorithms; data mining; domain experts; iterative evolutionary clustering approach; multiobjective genetic algorithm; natural clustering; user-specified criteria; validity indexes; Clustering algorithms; Computer science; Concurrent computing; Couplings; Genetic algorithms; Intelligent systems; Iterative methods; Scalability; Testing; Upper bound; classification; clustering; data mining; multi-objective genetic algorithm; partitioning; validity indexes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems, 2006 3rd International IEEE Conference on
Conference_Location :
London
Print_ISBN :
1-4244-01996-8
Electronic_ISBN :
1-4244-01996-8
Type :
conf
DOI :
10.1109/IS.2006.348468
Filename :
4155475
Link To Document :
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