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A Cultural Algorithm Based on Artificial Bee Colony Optimization for Community Detection in Signed Social Networks

机译:签名社区网络中基于人工蜂群优化的社区检测文化算法

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In this paper, we propose a cultural algorithm for detecting communities in signed networks based on artificial bee colony optimization, which is a process of dual inheritance from both a micro-evolutionary level and a macro-evolutionary level. We define the population space and belief space of the algorithm which are fit for community detection problem in signed social networks. To validate the performance of the algorithm we make experiments on two real-world networks and comparative experiments with three existing detecting algorithms on synthetic networks. The experimental results show that our algorithm gets a good performance on real-world networks and outperforms other algorithms on most of synthetic networks.
机译:在本文中,我们提出了一种基于人工蜂群优化的在签名网络中检测社区的文化算法,该算法是从微观进化层次和宏观进化层次双重继承的过程。我们定义了算法的人口空间和信念空间,它们适合于签名社会网络中的社区检测问题。为了验证算法的性能,我们在两个真实世界的网络上进行了实验,并在合成网络上使用了三种现有的检测算法进行了比较实验。实验结果表明,该算法在实际网络中具有良好的性能,在大多数合成网络中均优于其他算法。

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