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Fast computation of empirically tight bounds for the diameter of massive graphs
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Source Journal of Experimental Algorithmics (JEA) archive
Volume 13 ,  (February 2009) table of contents
SECTION: 1 - Regular Papers table of contents
Article No. 10  
Year of Publication: 2009
ISSN:1084-6654
Authors
Clémence Magnien  LIP6 -- CNRS and UPMC
Matthieu Latapy  LIP6 -- CNRS and UPMC
Michel Habib  LIAFA -- CNRS and Université Paris Diderot
Publisher
ACM  New York, NY, USA
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ABSTRACT

The diameter of a graph is among its most basic parameters. Since a few years ago, it moreover became a key issue to compute it for massive graphs in the context of complex network analysis. However, known algorithms, including the ones producing approximate values, have too high a time and/or space complexity to be used in such cases. We propose here a new approach relying on very simple and fast algorithms that compute (upper and lower) bounds for the diameter. We show empirically that, on various real-world cases representative of complex networks studied in the literature, the obtained bounds are very tight (and even equal in some cases). This leads to rigorous and very accurate estimations of the actual diameter in cases which were previously untractable in practice.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Latapy, M. and Magnien, C. 2008. Complex network measurements: Estimating the relevance of observed properties. To appear in the proceedings of ieee infocom.
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Watts, D. and Strogatz, S. 1998. Collective dynamics of small-world networks. Nature 393.
 
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Collaborative Colleagues:
Clémence Magnien: colleagues
Matthieu Latapy: colleagues
Michel Habib: colleagues