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A new ant colony clustering algorithm based on DBSCAN

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4 Author(s)
Shang Liu ; Coll. of Inf. Sci. & Technol., Nankai Univ., Tianjin, China ; Zhi-Tong Dou ; Fei Li ; Ya-Lou Huang

The AntClass algorithm is a new algorithm applying ant colony clustering algorithm to cluster analysis, and the result is satisfying. To attack the slow speed of the AntClass algorithm, a new algorithm named DBAntCluster is proposed. Firstly, the high density clusters are got in the dataset by using DBSCAN algorithm, and then these high density clusters are scattered in the grid board as a special kind of data object with other single data objects in the dataset. In DBAntCluster algorithm, the ants can avoid many unnecessary movements by using the data attribute of density and distribution well, and the speed is greatly accelerated. This improvement is validated in our experiments.

Published in:

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on  (Volume:3 )

Date of Conference:

26-29 Aug. 2004