基于改进蛙跳算法的社区划分方法

王桐; 赵昕琳

doi:10.3969/j.issn.1000-436x.2014.z2.008

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基于改进蛙跳算法的社区划分方法

学术论文 | 更新时间：2024-06-05

- 基于改进蛙跳算法的社区划分方法
- Improved shuffled frog-leaping algorithm based network community detection method
- 通信学报 2014年35卷第Z2期页码：48-52
- 作者机构：
  
  哈尔滨工程大学信息与通信工程学院，黑龙江哈尔滨 150001
- 作者简介：
  
  [ "王桐（1977-），男，黑龙江哈尔滨人，哈尔滨工程大学副教授，主要研究方向为无线网络、云计算与信息安全。" ]
  [ "赵昕琳（1990-），女，黑龙江哈尔滨人，哈尔滨工程大学硕士生，主要研究方向为社交网络，推荐系统。" ]
- 基金信息：
  
  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)
- DOI：10.3969/j.issn.1000-436x.2014.z2.008
  中图分类号： TP301.6
- 网络出版日期：2014-11，
  
  纸质出版日期：2014-11-30
- 稿件说明：
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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):48-52.

Tong WANG, Xin-lin ZHAO. Improved shuffled frog-leaping algorithm based network community detection method[J]. Journal on communications, 2014, 35(Z2): 48-52.
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):48-52. DOI： 10.3969/j.issn.1000-436x.2014.z2.008.

Tong WANG, Xin-lin ZHAO. Improved shuffled frog-leaping algorithm based network community detection method[J]. Journal on communications, 2014, 35(Z2): 48-52. DOI： 10.3969/j.issn.1000-436x.2014.z2.008.

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.

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Keywords

references

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