首页 | 官方网站   微博 | 高级检索  
     

基于边图的线性流重叠社区发现算法
引用本文:王斌,李强,盛津芳,孙泽军.基于边图的线性流重叠社区发现算法[J].计算机工程与应用,2019,55(2):60-66.
作者姓名:王斌  李强  盛津芳  孙泽军
作者单位:中南大学 信息科学与工程学院,长沙,410083;中南大学 信息科学与工程学院,长沙,410083;中南大学 信息科学与工程学院,长沙,410083;中南大学 信息科学与工程学院,长沙,410083
摘    要:重叠网络的社区发现是复杂网络研究中的重要问题。为了提高网络中重叠社区发现的时间效率,提出一种基于边图的线性流重叠社区发现算法LBSA。算法首先对于边图网络中的边进行随机的依次处理,完成节点的初步社区划分,再将其中重叠小社区合并到相似度最大的其他大社区中得到最终的社区。通过以上步骤,算法能够以接近线性的时间复杂度得到网络的重叠结构。从最终的实验结果来看,与其他算法相比,该算法能够在更短的时间有质量地发现网络中的重叠社区。

关 键 词:流式图  重叠社区发现  边聚类系数  边图  社区相似度

Linear Streaming Algorithm for Overlapping Community Detection Based on Link Graph
WANG Bin,LI Qiang,SHENG Jinfang,SUN Zejun.Linear Streaming Algorithm for Overlapping Community Detection Based on Link Graph[J].Computer Engineering and Applications,2019,55(2):60-66.
Authors:WANG Bin  LI Qiang  SHENG Jinfang  SUN Zejun
Affiliation:School of Information Science and Engineering, Central South University, Changsha 410083, China
Abstract:Overlapping community detection is a major topic in complex network research. To improve the time efficiency of detection overlapping communities in the network, it proposes a link-based streaming overlapping community detection algorithm called LBSA. The algorithm firstly deals with the edges of the link graph in random order to get the initial communities, then merges the small overlapping communities with other the most similarly large communities. Through those two steps, the algorithm can get the overlapping structure of network with nearly linear time complexity. Experimental results show that the algorithm can detect the overlapping communities in the network with better time efficiency and has good performance compared to the other algorithms.
Keywords:graph streaming  overlapping community detection  edge clustering coefficient  link graph  community similarity  
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号