Title :
Shaping Up Clusters with PSO
Author :
Breaban, Mihaela ; Luchian, Silvia
Author_Institution :
Fac. of Comput. Sci., Alexandru loan Cuza Univ., Iasi, Romania
Abstract :
This paper presents a method for enhancing the performance of current clustering algorithms; the method is based on Particle Swarm Optimization techniques. Namely, a preprocessing step aims at bringing rdquocloserrdquo objects which are likely to belong to the same cluster, while increasing the distance between objects likely to belong to different clusters. Experimental results show significantly improved performance for further clustering procedures especially when non-spherical clusters are involved.
Keywords :
particle swarm optimisation; pattern clustering; current clustering algorithm; particle swarm optimization; Algorithm design and analysis; Clustering algorithms; Clustering methods; Computer science; Euclidean distance; Particle swarm optimization; Partitioning algorithms; Scientific computing; Shape measurement; Size measurement; PSO; clustering;
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing, 2008. SYNASC '08. 10th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-0-7695-3523-4
DOI :
10.1109/SYNASC.2008.70
