[1]张璋,张然,朱东生. 关系数据库中社区发现方法研究[J].计算机技术与发展,2014,24(08):108-111.
　ZHANG Zhang,ZHANG Ran,ZHU Dong-sheng. Research on Community Discovery Methods in Relational Database[J].,2014,24(08):108-111.
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 关系数据库中社区发现方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年08期
页码:
108-111
栏目:
智能、算法、系统工程
出版日期:
2014-08-10

文章信息/Info

Title:
 Research on Community Discovery Methods in Relational Database
文章编号:
1673-629X（2014）08-0108-04
作者:
 张璋; 张然; 朱东生
 长沙理工大学 计算机与通信工程学院
Author(s):
 ZHANG Zhang; ZHANG Ran; ZHU Dong-sheng
关键词:
 ; 社区发现; 加权网络; 分布式数据库
Keywords:
 ; community discovery; weighted networks; distributed database
分类号:
TP301
文献标志码:
A
摘要:
 文中在研究了现有社区发现算法的基础上，提出了一种简单的加权网络中社区发现方法。文中基于社区结构最为普遍的性质，受社会网络中真实社区结构和并行计算的任务划分规则的启发，提出了基于核心边的加权网络中社区发现方法。该方法首先依据网络中边的权值寻找核心边；然后依据相似性度量，发现网络中的一个初始社区；最后通过隶属度度量，将发现的初始社区逐步扩展成网络中的社区结构。该方法在进行社区结构发现的过程中，仅仅依赖节点所处位置的局部信息，可以在对网络进行广度优先遍历的过程中完成社区发现工作。因此该方法具有较低的计算复杂度，可以适用于大规模网络中的社区发现。通过有效性实验和效率实验，表明该方法可以有效发现大规模网络中的社区结构。
Abstract:
 A simple weighted community discovery algorithm is proposed based on study of existing community discovery methods. Based on the most commonly nature of community structures,inspired by task division rules of the real community structure and parallel compu-ting in social networks,propose the weighted network community discovery methods based on core edge. In this method,based on the weight of edges in the network,look for the core edge;then in accordance with similarity measure,find an initial community in the net-work;finally through membership metrics,you will find the initial community gradually expands into community structures in a network. This method during the discovery process of community structures,relies solely on the local node location information,the network can be a breadth-first traversal of the community discovery process to complete the work. Therefore,the method has a low computational com-plexity,which can be applied in a large-scale network community discovery. Through experimental test on effectiveness and efficiency, the method can effectively detect large-scale network of community structures.

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更新日期/Last Update: 2015-03-26