NDLI: Détection de communautés , étude comparative sur graphes reels

Content Provider	Semantic Scholar
Author	Navarro, Emmanuel Cazabet, Rémy
Copyright Year	2010
Abstract	Several community detection algorithms have been pr oposed in last years. Usually, the evaluation of these algori thms consist in identifying communities in generated graphs, not ne cessarily realistic. In this paper, we try to compare their r sults on large real world graphs. As we don’t know the correct decompos ition in communities of large real graph, we first compare r esults of the different algorithms between them, and then the rob ustness of their results when graphs are rewired. This allow us to c onclude that, on one hand, communities of real graphs are harder to detect than the ones of generated graphs and, on the other hand, cu rrent state of the art algorithms did not converge on a unique sol ution, unlike what happen on generated graphs. Key-words: Community detection, complex networks, evaluation
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.quaero.org/media/files/bibliographie/navarroetal_marami2010.pdf
Alternate Webpage(s)	http://www.irit.fr/journal-i3/volume11/numero01/revue_i3_11_01_05_en.pdf
Alternate Webpage(s)	http://enavarro.me/papers/2010/navarroEtAl-MARAMI2010-slides.pdf
Alternate Webpage(s)	https://enavarro.me/papers/2010/navarroEtAl-MARAMI2010.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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