Constrained clustering via swarm intelligence

Authors:
Xiaohua Xu;Zhoujin Pan;Ping He;Ling Chen
Affiliations:
Department of Computer Science and Engineering, Yangzhou University, Yangzhou, China;Department of Computer Science and Engineering, Yangzhou University, Yangzhou, China;Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China;Department of Computer Science and Engineering, Yangzhou University, Yangzhou, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Year:
2011

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Abstract

This paper investigates the constrained clustering problem through swarm intelligence. We present an ant clustering algorithm based on random walk to deal with the pairwise constrained clustering problems. Our algorithm mimics the behaviors of the real-world ant colonies and produces better clustering result on both synthetic and UCI datasets compared with the unsupervised ant-based clustering algorithm and the cop-kmeans algorithm.