通信学报
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王 桐,赵昕琳
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摘要: 现有的网络社区划分方法以社区为主体,机械地将每一个节点划分到某一个社区,在真实网络中,对于活跃度低的用户进行划分会大大降低划分精确度,同时增加时间复杂度,并具有较小的划分意义。因此,将蛙跳算法与社区划分相结合,通过对青蛙性能的排序,提取活跃度高的用户,从而提高划分精确度。实验结果表明该方法具有良好的性能。
Abstract: Existing community method aims to divide nodes into a community mechanically. In a real network, it will reduce the classification accuracy greatly for the low active users, while increasing the time complexity. It has small significance. Therefore, this paper will combine shuffled leap-frog algorithm with community detection method. It will extract active users by sorting on properties of frog, so as to improve the efficiency of division. Experimental results show that the method has good performance.
王 桐,赵昕琳. 基于改进蛙跳算法的社区划分方法[J]. 通信学报.
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https://www.infocomm-journal.com/txxb/CN/Y2014/V35/IZ2/8