| 基于改进蛙跳算法的社区划分方法 |
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| 引用本文： | 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,2014,35(Z2):8-52. |
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| 作者姓名： | 王 桐 赵昕琳 |
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| 作者单位： | 哈尔滨工程大学 信息与通信工程学院，黑龙江 哈尔滨 150001 |
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| 基金项目： | 国家自然科学基金资助项目(61102105)；中国博士后科学基金资助项目(20080440840)；教育部博士点基金资助项目(20102304120014)；黑龙江省自然科学基金资助项目(F201029) |
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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。
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| 关 键 词： | 社交网络 社区划分 蛙跳算法 社区结构 |
Improved shuffled frog-leaping algorithm based
network community detection method |
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| Tong WANG,Xin-lin ZHAO.Improved shuffled frog-leaping algorithm based
network community detection method[J].Journal on Communications,2014,35(Z2):8-52. |
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| Authors: | Tong WANG Xin-lin ZHAO |
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| Affiliation: | College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China |
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| 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. |
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| Keywords: | social networks community detection shuffled frog-leaping algorithm community structures |
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