Research Article
PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 107 - Issue 1 |
| Published: December 2014 |
| Authors: Raheleh Biglari, Alireza Bagheri |
10.5120/18715-9934
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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 },
year = { 2014 },
volume = { 107 },
number = { 1 },
pages = { 22-26 },
doi = { 10.5120/18715-9934 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Raheleh Biglari
%A Alireza Bagheri
%T PPreDeCon: A Parallel version of Preference Density Connected Clustering Algorithm%T
%J International Journal of Computer Applications
%V 107
%N 1
%P 22-26
%R 10.5120/18715-9934
%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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