In this topic? What is best criterio to consider if a network is dense or 
sparse? I think is not easy to identify this frontier!

Manuel 
=================================
Dr. Manuel J.  Zetina-Rejón
Interdisciplinary Center of Marine Sciences National Polytechnic
Institute Marine Biology and Fisheries Department
Av. IPN S/N Col. Playa Palo de Sta. Rita La Paz, BCS, Mexico
AP 590
Tel. +52 (612) 1225344 Fax. +52(612) 1225322
http://www.cicimar.ipn.mx
=================================

> El 24/10/2014, a las 10:57, Tamas Nepusz <[email protected]> escribió:
> 
>> Then I want to apply a community detection algorithm which will evaluate
>> graph structure mainly on edges' weights.
> All the community detection algorithms in igraph are designed for sparse
> networks, so if you want to use any of them, you have to convert your matrix 
> to
> a sparse one first. This can be done in multiple ways; e.g., you could drop 
> the
> connections below a certain weight, or you could keep the best (i.e. highest
> weight) connections for each of your vertices. Then you can use whichever
> algorithm you prefer from igraph.
> 
> If you want to keep your dense graph, you could try MCL [1] or spectral
> clustering [2], but these are not implemented in igraph.
> 
> [1]: http://micans.org/mcl
> [2]: http://en.wikipedia.org/wiki/Spectral_clustering
> 
> T.
> 
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