DocumentCode
3507709
Title
Ant Colony Optimization and Data Mining: Techniques and Trends
Author
Michelakos, Ioannis ; Mallios, Nikolaos ; Papageorgiou, Elpiniki ; Vassilakopoulos, Michael
Author_Institution
Dept. of Comput. Sci. & Biomed. Inf., Univ. of Central Greece, Lamia, Greece
fYear
2010
fDate
4-6 Nov. 2010
Firstpage
284
Lastpage
289
Abstract
The Ant Colony Optimization (ACO) technique was inspired by the ants´ behaviour throughout their exploration for food. The use of this technique has been very successful for several problems. Besides, Data Mining (DM) has emerged as an important technology with numerous practical applications, due to the wide availability of a vast amount of data. The collaborative use of ACO and DM is very promising. In this paper, we review ACO, DM, Classification and Clustering (popular DM tasks) and focus on the use of ACO for Classification and Clustering. Moreover, we briefly present related applications and examples and outline possible future trends of this promising collaborative use of techniques.
Keywords
data mining; optimisation; pattern classification; pattern clustering; ant colony optimization; data mining; pattern classification; pattern clustering; Ant Colony Optimization (ACO); Classification; Clustering; Data Mining;
fLanguage
English
Publisher
ieee
Conference_Titel
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2010 International Conference on
Conference_Location
Fukuoka
Print_ISBN
978-1-4244-8538-3
Electronic_ISBN
978-0-7695-4237-9
Type
conf
DOI
10.1109/3PGCIC.2010.47
Filename
5662775
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