文献类型：会议论文

英文题名：Entanglement partitioning of quantum particles for data clustering

作者：Shuai, Dianxun[1];Lu, Cunpai[1];Zhang, Bin[1]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China

会议论文集：30th Annual International Computer Software and Applications Conference

会议日期：SEP 17-21, 2006

会议地点：Chicago, IL

语种：英文

外文关键词：Computer simulation - Data structures - Mathematical models

摘要：This paper presents a generalized quantum particle model to greatly quicken and improve data clustering. I ne 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.