Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:Zhongnan Daxue Xuebao (Ziran Kexue Ban)

Abstract:The purpose was to improve the efficiency of local density and delta distance based clustering (DDC) by using the quantum computation, which was characterized by the great performance of the parallel computation. First, the quantum counting algorithm was developed to accelerate the processing of local density for each data point. Then, the quantum algorithm for finding the minimum was incorporated to find each point’s delta distance. The results show that the efficiency of DDC can be improved significantly by using quantum computation to accelerate DDC algorithm. © 2018, Central South University Press. All right reserved.

ISSN No.:1672-7207

Translation or Not:no

Date of Publication:2018-07-26

Co-author:Liu, Xuejuan,Xu Juan,Duan, Bojia

Correspondence Author:Liu, Xuejuan,Yuan Jiabing