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Huang, Z.X. (1997) Clustering Large Data Sets with Mixed Numeric and Categorical Values. Proceedings of the First Pacific Asia Knowledge Discovery and Data Mining Conference, Singapore, World Scientific, 21-34.

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• TITLE: Clustering Algorithm of Quantum Self-Organization Network

  AUTHORS: Ziyang Li, Panchi Li

  KEYWORDS: Quantum Bits, Bloch Spherical Rotation, Self-Organization Network, Clustering Algorithm

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.5 No.6, June 16, 2015

  ABSTRACT: To enhance the clustering ability of self-organization network, this paper introduces a quantum inspired self-organization clustering algorithm. First, the clustering samples and the weight values in the competitive layer are mapped to the qubits on the Bloch sphere, and then, the winning node is obtained by computing the spherical distance between sample and weight value. Finally, the weight values of the winning nodes and its neighborhood are updated by rotating them to the sample on the Bloch sphere until the convergence. The clustering results of IRIS sample show that the proposed approach is obviously superior to the classical self-organization network and the K-mean clustering algorithm.