Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

May 7, 2012

Clusters & Communities (overlapping dense groups in networks)

Filed under: CFinder,Clustering,Networks — Patrick Durusau @ 7:18 pm

Clusters & Communities (overlapping dense groups in networks) (CFinder)

From the webpage:

CFinder is a free software for finding and visualizing overlapping dense groups of nodes in networks, based on the Clique Percolation Method (CPM) of Palla et. al., Nature 435, 814-818 (2005). CFinder was recently applied to the quantitative description of the evolution of social groups: Palla et. al., Nature 446, 664-667 (2007).

CFinder offers a fast and efficient method for clustering data represented by large graphs, such as genetic or social networks and microarray data. CFinder is also very efficient for locating the cliques of large sparse graphs.

I rather like the title for the webpage as opposed to simply CFinder, which is what I started to use. Would be accurate but also wouldn’t capture the notion of discovering overlapping dense groups in networks.

Whether we realize it or not, the choice of a basis for relationships can produce or conceal any number of dense overlapping groups in a network.

I have mentioned CFinder elsewhere but wanted to call it out, in part to raise its position on my horizon.

Parallel clustering with CFinder

Filed under: CFinder,Clustering,Networks,Parallel Programming — Patrick Durusau @ 7:18 pm

Parallel clustering with CFinder by Peter Pollner, Gergely Palla, and Tamas Vicsek.

Abstract:

The amount of available data about complex systems is increasing every year, measurements of larger and larger systems are collected and recorded. A natural representation of such data is given by networks, whose size is following the size of the original system. The current trend of multiple cores in computing infrastructures call for a parallel reimplementation of earlier methods. Here we present the grid version of CFinder, which can locate overlapping communities in directed, weighted or undirected networks based on the clique percolation method (CPM). We show that the computation of the communities can be distributed among several CPU-s or computers. Although switching to the parallel version not necessarily leads to gain in computing time, it definitely makes the community structure of extremely large networks accessible.

If you aren’t familiar with CFinder, you should be.

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