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PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm

by Raheleh Biglari, Alireza Bagheri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 1
Year of Publication: 2014
Authors: Raheleh Biglari, Alireza Bagheri
10.5120/18715-9934

Raheleh Biglari, Alireza Bagheri . PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm. International Journal of Computer Applications. 107, 1 ( December 2014), 22-26. DOI=10.5120/18715-9934

@article{ 10.5120/18715-9934,
author = { Raheleh Biglari, Alireza Bagheri },
title = { PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 1 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number1/18715-9934/ },
doi = { 10.5120/18715-9934 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:39:55.810472+05:30
%A Raheleh Biglari
%A Alireza Bagheri
%T PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 1
%P 22-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Clustering is one of the major techniques in data mining. PreDeCon is a density-based clustering algorithm for computing clusters of spatial objects. In this paper, PPreDeCon is presented as a parallel version of this algorithm in shared memory model. The theoretical analysis and experimental results show that PPreDeCon offers nearly linear speedup while keeps other advantages of PreDeCon.

References
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Index Terms

Computer Science
Information Sciences

Keywords

clustering algorithms parallel algorithms spatial databases density-based clustering shared memory model.

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