A Nature-Inspired Metaheuristic Cuckoo Search Algorithm for Community Detection in Social Networks",

Citation:
Babers, R., and A. E. Hassanien, " A Nature-Inspired Metaheuristic Cuckoo Search Algorithm for Community Detection in Social Networks", ", International Journal of Service Science, Management, Engineering, and Technology, IJSSMET , vol. 8, issue 1, pp. 50-, 2017.

Abstract:

In last few years many approaches have been proposed to detect communities in social networks using diverse ways. Community detection is one of the important researches in social networks and graph analysis. This paper presents a cuckoo search optimization algorithm with Lévy flight for community detection in social networks. Experimental on well-known benchmark data sets demonstrates that the proposed algorithm can define the structure and detect communities of complex networks with high accuracy and quality. In addition, the proposed algorithm is compared with some swarms algorithms including discrete bat algorithm, artificial fish swarm, discrete Krill Herd, ant lion algorithm and lion optimization algorithm and the results show that the proposed algorithm is competitive with these algorithms.

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