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Exacting eccentricity for small-world networks
Authors
L Chang
W Li
+4 more
X Lin
M Qiao
L Qin
Y Zhang
Publication date
24 October 2018
Publisher
'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Cite
Abstract
© 2018 IEEE. This paper studies the efficiency issue on computing the exact eccentricity-distribution of a small-world network. Eccentricity-distribution reflects the importance of each node in a graph, which is beneficial for graph analysis. Moreover, it is key to computing two fundamental graph characters: diameter and radius. Existing eccentricity computation algorithms, however, are either inefficient in handling large-scale networks emerging nowadays in practice or approximate algorithms that are inappropriate to small-world networks. We propose an efficient approach for exact eccentricity computation. Our approach is based on a plethora of insights on the bottleneck of the existing algorithms-one-node eccentricity computation and the upper/lower bounds update. Extensive experiments demonstrate that our approach outperforms the state-of-The-Art up to three orders of magnitude on real large small-world networks
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OPUS - University of Technology Sydney
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Last time updated on 18/10/2019
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Last time updated on 10/08/2021