查询结果:   赵文涛,赵好好,孟令军.基于相关拓扑势的社团发现算法[J].计算机应用与软件,2017,34(1):258 - 262,269.
中文标题
基于相关拓扑势的社团发现算法
发表栏目
算法
摘要点击数
530
英文标题
COMMUNITY DETECTION ALGORITHM BASED ON INTERRELATED TOPOLOGICAL POTENTIAL
作 者
赵文涛 赵好好 孟令军 Zhao Wentao Zhao Haohao Meng Lingjun
作者单位
河南理工大学计算机科学与技术学院 河南 焦作 454000 河南省普通高等学校矿山信息化研究重点实验室 河南 焦作 454000    
英文单位
School of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454000,Henan,China Key Laboratory of Mine Information Research at General Universities in Henan Province,Jiaozuo 454000,Henan,China    
关键词
社团结构 复杂网络 相关拓扑势 标签传播
Keywords
Community structure Complex network Interrelated topological potential Label propagation
基金项目
河南省科技攻关计划项目(142102210435);河南省高等学校矿山信息化重点学科开放实验室开放基金项目(ky2012-02)
作者资料
赵文涛,教授,主研领域:数据库,数据挖掘,大数据。赵好好,硕士生。孟令军,硕士生。 。
文章摘要
针对传统算法社团划分精度较低以及模块度函数分辨率低的问题,提出一种基于相关拓扑势的社团发现算法,简称BITP算法。该算法考虑节点的相关性因素,引入相关拓扑势来衡量节点的影响力,寻找出其中的极大势值点,采用标签传播的思想对社团的规模进行控制。在人工合成网络和真实网络上,与多种算法进行实验对比,结果表明该算法多次运行结果相对稳定且社团划分精度较高。算法时间复杂度为O(n),且不需要先验知识,更适合大规模复杂网络上的社团结构挖掘。
Abstract
Since the traditional methods obtain low precision in division and low resolution in module function, an algorithm of community detection BITP is proposed based on the interrelated topological potential. The algorithm introduces the interrelated topological potential to evaluate the influence of nodes by considering the correlation factor between nodes. The nodes with extreme potential are searched at first. The sizes of the local communities are controlled by adopting the method of label propagation. The experimental results on synthetic and real-world networks show that the proposed algorithm is relatively stable and achieves higher precision. It is more suitable for detecting community structure in large-scaled and complex networks with a time complexity of O(n) and no prior knowledge.
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