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Author Nagarajan, Chandrashekhar ♦ Williamson, David P.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Abstract In this article, we consider different incremental and hierarchical $\textit{k}-median$ algorithms with provable performance guarantees and compare their running times and quality of output solutions on different benchmark $\textit{k}-median$ datasets. We determine that the quality of solutions output by these algorithms for all the datasets is much better than their performance guarantees suggest. Since some of the incremental $\textit{k}-median$ algorithms require approximate solutions for the $\textit{k}-median$ problem, we also compare some of the existing $\textit{k}-median$ algorithms running times and quality of solutions obtained on these datasets.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-11-01
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 18
Page Count 21
Starting Page 3.1
Ending Page 3.21


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Source: ACM Digital Library