Author : NEVEEN IBRAHIM MOHAMED GHALI
CoAuthors : Amany A. Naem
Source : Bulletin of Electrical Engineering and Informatics
Date of Publication : 12/2019
Abstract :
Antlion Optimization (ALO) is one of the latest population based
optimization methods that proved its good performance in a variety of
applications. The ALO algorithm copies the hunting mechanism of antlions
to ants in nature. Community detection in social networks is conclusive to
understanding the concepts of the networks. Identifying network
communities can be viewed as a problem of clustering a set of nodes into
communities. k-median clustering is one of the popular techniques that has
been applied in clustering. The problem of clustering network can be
formalized as an optimization problem where a qualitatively objective
function that captures the intuition of a cluster as a set of nodes with better in
ternal connectivity than external connectivity is selected to be optimized. In
this paper, a mixture antlion optimization and k-median for solving the
community detection problem is proposed and named as K-median
Modularity ALO. Experimental results which are applied on real life
networks show the ability of the mixture antlion optimization and k-median
to detect successfully an optimized community structure based on putting the
modularity as an objective function.
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