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Advances in Rough and Soft Clustering: Meta-Clustering, Dynamic Clustering, Data-Stream Clustering Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Discrete Group Search Optimizer for Community Detection in Social Networks

Authors : Moustafa Mahmoud Ahmed, Mohamed M. Elwakil, Aboul Ella Hassanien, Ehab Hassanien

Published in: Rough Sets

Publisher: Springer International Publishing

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Abstract

Discovering community structure in complex networks has been intensively investigated in recent years. Community detection can be treated as an optimization problem in which an objective fitness function is optimized. Intuitively, the objective fitness function captures the subgraphs in the network that has densely connected nodes with sparse connections between subgraphs. In this paper, we propose Discrete Group Search Optimizer (DGSO) which is an efficient optimization algorithm to solve the community detection problem without any prior knowledge about the number of communities. The proposed DGSO algorithm adopts the locus-based adjacency representation and several discrete operators. Experiments in real life networks show the capability of the proposed algorithm to successfully detect the structure hidden within complex networks compared with other high performance algorithms in the literature.

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previous chapter Exploiting Group Pairwise Preference Influences for Recommendations
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Metadata
Title
Discrete Group Search Optimizer for Community Detection in Social Networks
Authors
Moustafa Mahmoud Ahmed
Mohamed M. Elwakil
Aboul Ella Hassanien
Ehab Hassanien
Copyright Year
2016
Book
Rough Sets

Print ISBN: 978-3-319-47159-4

Electronic ISBN: 978-3-319-47160-0

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-47160-0_40

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