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基于隐马尔可夫随机场的社区结构发现算法
引用本文:刘栋,刘震,张贤坤. 基于隐马尔可夫随机场的社区结构发现算法[J]. 计算机工程与设计, 2012, 33(9): 3481-3484
作者姓名:刘栋  刘震  张贤坤
作者单位:1. 河南师范大学计算机与信息技术学院,河南新乡,453007
2. 河南科技学院网络信息中心,河南新乡,453000
3. 天津科技大学计算机科学与信息工程学院,天津,300222
基金项目:天津市科技型中小企业创新基金项目(11ZXCXGX07700)
摘    要:针对社区结构发现问题,提出了一种基于隐马尔可夫随机场社区发现算法.该方法将网络中的顶点度数映射为顶点信息值,用马尔可夫随机场模型描述网络中上下文信息并构造系统能量函数,使用迭代条件模式算法对能量方程进行优化.该方法在Zachary空手道俱乐部网络、海豚关系网络以及美国大学足球联赛网络上进行验证,实验结果表明,该算法的准确率较高.

关 键 词:社区发现  隐马尔可夫随机场  复杂网络  顶点度数  迭代条件模式

Community structure detection algorithm based on hidden Markov random field
LIU Dong , LIU Zhen , ZHANG Xian-kun. Community structure detection algorithm based on hidden Markov random field[J]. Computer Engineering and Design, 2012, 33(9): 3481-3484
Authors:LIU Dong    LIU Zhen    ZHANG Xian-kun
Affiliation:1.College of Computer and Information Technology,Henan Normal University,Xinxiang 453007,China;2.Network and Information Center,Henan Institute of Science and Technology,Xinxiang 453000,China;3.College of Computer Science and Information Engineering,Tianjin University of Science and Technology,Tianjin 300222,China)
Abstract:For the problem of community structure detection of complex network,a community detection algorithm based on hidden Markov random field is presented.In this method,the network vertices information value corresponding to its degree is assumed,the HMRF model is applied to characterize the contexture-dependent information,and the energy function of system is defined,iterated conditional mode algorithm is applied to fulfill optimization.The algorithm is tested on Zachary karate clue network,dolphin social network and American College football network,and experimental result shows it has high accuracy rate.
Keywords:community detection  hidden Markov random field  complex network  vertex degree  iterated conditional modes
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