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Unformatted text preview: . Hoefer, Z. Nikoloski, and
D. Wagner, On modularity clustering, IEEE Transactions on Knowledge and
Data Engineering, 20 (2008), 172188.
• So rather than ﬁnding THE optimal partitioning, we turn to approximation
algorithms to ﬁnd approximately optimal partitions. The Louvain method
• V.D. Blondel, J.-L. Guillaume, R. Lambiotte and E. Lefebvre (2008). ”Fast
unfolding of community hierarchies in large networks”. J. Stat. Mech.:
• The method consists of two phases. First, it looks for ”small” communities
by optimizing modularity in a local way. Second, it aggregates nodes
of the same community and builds a new network whose nodes are the
communities. These steps are repeated iteratively until a maximum of
modularity is attained.
• This method is implemented NetworkX and others. Dendrograms Can be built by aggregating (Louvain method) or recursing from the full graph. ´
enyi2, Illes Farkas1 & Tamas Vicsek1,2 Overlapping communities! re and society can be described in
with the overlaps being their links. The number of such links of
the intricate web of connections
community a can be called its community degree, dcom : Finally, the
A Palla, is Dernyi, I. Farkas, and can most naturally be deﬁned as the
size scom of any community a T. Vicsek, Uncovering the
e of1–4.G.key question I. how to
tion of such networks as the conumber of its nodes. To characterize the community structure of a
ubunitscommunity structure of complex networks in nature and society,
large network we introduce the distributions of these four basic
ed parts. Identifying these a priori
quantities. In particular we focus on their cumulative distribution
(2005), 814818. ,
as functionally related proteins
p s o f p eo ple 8 , 9 ) i s c r u c ia l to t he
ral and functional proper ties of
inistic methods used for large netities, whereas most of the actual
overlapping cohesive groups of
approach to analysing the main
woven sets of overlapping commus uncovering the modular structure
ﬁning a set of new characteristic
communities, we apply an efﬁcient
ping communities on a large scale.
niﬁcant, and the distributions we
tures of n...
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- Winter '11