Title :
MST Clustering Algorithm Based on Optimized Grid
Author :
Jianliang Meng ; Weixiang Cheng
Author_Institution :
Dept of Comput., North China Electr. Power Univ., Baoding
Abstract :
A MST clustering algorithm based on optimized grid (OGMST) is presented. On one hand,the OGMST dealt with datasets by the way of MST, on the other hand,it resolved the MST algorithm´s limitation of unfit for multi-density datasets by the use of parameter automatic grid paritition technique and density threshold method, and it improved the efficiency and precision of the existed clustering algorithms on mult-density datasets. Besides, the OGMST can extract border points effectively. The experiment results show that the OGMST is of good extensible ability and can reduce running-time.
Keywords :
grid computing; pattern clustering; MST clustering algorithm; density threshold method; multi-density datasets; optimized grid; parameter automatic grid paritition technique; Clustering algorithms; Data mining; Distributed computing; Grid computing; Nearest neighbor searches; Partitioning algorithms; Power systems; Signal processing algorithms; Signal resolution; MST; center points; grid-based;
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3278-3
DOI :
10.1109/IIH-MSP.2008.52