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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 based on random walk to deal with the constrained clustering problems with pairwise must-link and cannot-link constraints. Experimental results show that our approach is more effective on both synthetic datasets and UCI datasets compared with the cop-kmeans algorithm and ant-based clustering algorithm.

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