DocumentCode :
2910308
Title :
Issues of grid-cluster retrievals in swarm-based clustering
Author :
Tan, Swee Chuan ; Ting, Kai Ming ; Teng, Shyh Wei
Author_Institution :
Gippsland Sch. of Inf. Technol., Monash Univ., Clayton, VIC
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
511
Lastpage :
518
Abstract :
One common approach in swarm-based clustering is to use agents to create a set of clusters on a two-dimensional grid, and then use an existing clustering method to retrieve the clusters on the grid. The second step, which we call grid-cluster retrieval, is an essential step to obtain an explicit partitioning of data. In this study, we highlight the issues in grid-cluster retrievals commonly neglected by researchers, and demonstrate the non-trivial difficulties involved. To tackle the issues, we then evaluate three methods: K-means, hierarchical clustering (Weighted Single-link) and density-based clustering (DBScan). Among the three methods, DBScan is the only method which has not been previously used for grid-cluster retrievals, yet it is shown to be the most suitable method in terms of effectiveness and efficiency.
Keywords :
data mining; particle swarm optimisation; pattern clustering; data partitioning; density-based clustering; grid-cluster retrievals; hierarchical clustering; swarm-based clustering; two-dimensional grid; Animals; Birds; Clustering algorithms; Clustering methods; Humans; Information retrieval; Insects; Inspection; Partitioning algorithms; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4630845
Filename :
4630845
Link To Document :
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