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Improving constrained clustering via swarm intelligence
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DOI：10.1016/j.neucom.2012.03.031.png)
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By simulating the clustering behavior of the real-world ant colonies, we propose in this paper a constrained ant clustering algorithm. This algorithm is embedded with the heuristic walk mechanism based on random walk to deal with the constrained clustering problems given pairwise must-link and cannot-link constraints. Experimental results show that our approach is more effective on both the synthetic datasets and the real datasets compared with the Cop-Kmeans and ant-based clustering algorithm. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Ant-based clustering
Constrained clustering
Random walk
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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