Volume 13 Number 3 (Mar. 2018)
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JSW 2018 Vol.13(3): 168-179 ISSN: 1796-217X
doi: 10.17706/jsw.13.3.168-179

Optimization of Density Peak Clustering Algorithm Based on OpenMP

Anbo Qiu, Zhuowei Wang*
School of Computer, Guangdong University of Technology, Guangzhou 510006,China

Abstract—The density peak clustering algorithm(CFSFDP) is a new clustering algorithm that implements simple, clustering non-spherical data sets. The algorithm needs artificial selection of clustering center,it is difficult to get the actual clustering centers accurately and can not effectively deal with various data sets. And the density calculation processhas nonlinear time complexity. In response to the above problems, a threshold-based parallel optimization CFSFDP (PT-CFSFDP) algorithm is proposed, which sets the threshold for the local density of samples and the distance to the points with higher local density, the sample point is selected as the cluster center whenthe parameter is greater than the threshold. The distance matrix is optimized in parallel with OpenMP. Experiments show that the PT-CFSFDP algorithm can get the clustering center accurately, the accuracy of the clustering results is up to 94% and the speedup of the algorithm is up to 4.25.

Index Terms—Density peaks, clustering centers, OpenMP, accuracy, speedup.


Cite: Anbo Qiu, Zhuowei Wang, "Optimization of Density Peak Clustering Algorithm Based on OpenMP," Journal of Software vol. 13, no. 3, pp. 168-179, 2018.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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