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30th Annual International Computer Software and Applications Conference (COMPSAC'06)
Entanglement Partitioning of Quantum Particles for Data Clustering
Chicago, Illinois
September 17-September 21
ISBN: 0-7695-2655-1
Dianxun Shuai, East China University of Sci. and Tech., China
Cunpai Lu, East China University of Sci. and Tech., China
Bin Zhang, East China University of Sci. and Tech., China
This paper presents a generalized quantum particle model to greatly quicken and improve data clustering. 1 The proposed model uses the random dynamics and quantum entanglement of quantum particles on a particle array. In comparison with classical nonquantum methods, the quantum particle model not only clusters much faster, but also has better clustering quality for multi-shape multidistribution high-dimensional large-scale data sets with noise. The simulations and comparisons show the effectiveness of the quantum particle model.
Citation:
Dianxun Shuai, Cunpai Lu, Bin Zhang, "Entanglement Partitioning of Quantum Particles for Data Clustering," compsac, vol. 2, pp.285-290, 30th Annual International Computer Software and Applications Conference (COMPSAC'06), 2006
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