Community Detection in Complex Networks Using Improved Artificial Bee Colony Algorithm

摘要

With more and more various systems in nature and society are proved to be modeled as complex networks, community detection in complex networks as a fundamental problem becomes a hot research topic in a large scale of subjects. Artificial Bee Colony Algorithm (ABC) has high efficiency and does not require any prior knowledge about the number or the original division of the communities. So it is suitable to solve complex clustering problems. We propose an improved ABC algorithm which modifies the number of initial food sources and dynamically adjusts search scope. Experimental results show that our algorithm can discover communities effectively by the classic Zachary Karate Club network. By comparative experiments, the improved artificial bee colony algorithm outperforms the traditional ABC algorithm in complex network.