Abstract
Discovering communities in complex environment is an interesting topic for many scientists. It becomes the mainstream issue in different research fields such as the web mining, biological networks and social networks. In this study, we propose a multi swarm version of Bee Swarm Optimization (BSO) algorithm for community detection problem with local search function called BSOCD-LS. The proposed algorithm considers the modularity Q for both local and global function. Additionally, the proposed method employs new technique to produce the reference solution and the taboo list to avoid stagnation. The experiments were carried out on real networks and compared to some representative methods. The results show that our proposed algorithm provide competitive results in term of modularity.
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Belkhiri, Y., Kamel, N., Drias, H. (2019). Multi-swarm BSO Algorithm with Local Search for Community Detection Problem in Complex Environment. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_28
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