DocumentCode
2338060
Title
An incremental clustering algorithm based on swarm intelligence theory
Author
Chen, Zhuo ; Meng, Qing-Chun
Author_Institution
Dept. of Comput. Sci., Ocean Univ. of China, Qingdao, China
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1768
Abstract
Although many clustering algorithms have been proposed so far, they seldom focused on high-dimensional and incremental databases. We present a new type of incremental clustering algorithm, which is based on the swarm intelligence theory. The new type of incremental clustering algorithm implements the clustering process by the actions of clustering agents. The clustering agents, which move in a three-dimensional space, have the abilities of memory, communication, analysis, judgement, coordination and so on. This new type of incremental clustering algorithm is applicable in periodically incremental environment. Experimental results have shown that this algorithm has many merits such as insensitivity to the order of the data, capability of dealing with the exceptional, high-dimensional and complicated data.
Keywords
cooperative systems; data mining; deductive databases; learning (artificial intelligence); pattern clustering; clustering agents; incremental clustering algorithm; incremental databases; incremental environment; swarm intelligence theory; three dimensional space; Clustering algorithms; Computer science; Data mining; Deductive databases; Intelligent systems; Machine learning algorithms; Marine technology; Oceans; Particle swarm optimization; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382062
Filename
1382062
Link To Document