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WorldCist'17 - 5th World Conference on Information Systems and Technologies

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Bee Swarm Optimization for Community Detection in Complex Network

Studying the topology of complex networks has attracted many scientists in recent years. It has been widely used in different fields, such as protein function prediction, web community mining and link prediction in many area. In this paper, we propose an algorithm based on the BSO ( bee swarm optimization) for community detection problem we call BSOCD. This algorithm takes modularity Q as objective function and K number of bees to create search area. In addition, the algorithm uses a new random strategy to generate the reference solution and the taboo list to avoid cycles during the research process. We validate our algorithm by testing it on real networks and compare its results with some other representative algorithms to check its efficiency.

Author(s):

Youcef Belkhiri    
University of Science and Technology Houari Boumediene
Algeria

Nadjet Kamel    
University Ferhat Abbas of Setif 1
Algeria

Habiba Drias    
University of Science and Technology Houari Boumediene
Algeria

Sofiane Yahiaoui    
University of Science and Technology Houari Boumediene
Algeria

 

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