Classification method in complex networks based on Semi-supervising

doi:10.3778/j.issn.1002-8331.2011.04.013

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (4): 47-49.DOI: 10.3778/j.issn.1002-8331.2011.04.013

• 研究、探讨 • Previous Articles Next Articles

Classification method in complex networks based on Semi-supervising

KONG Jian1，XIE Fuding1，SUN Yan1，ZHAO Fengxia2

1.College of Computer and Information，Liaoning Normal University，Dalian，Liaoning 116081，China
2.Qinhuangdao Vocational College，Qinhuangdao，Hebei 066100，China

Received:2009-06-08 Revised:2009-07-28 Online:2011-02-01 Published:2011-02-01
Contact: KONG Jian

半监督模式下复杂网络分类的方法

孔健¹，谢福鼎¹，孙岩¹，赵凤霞²

1.辽宁师范大学计算机与信息学院，辽宁大连 116081
2.秦皇岛职业技术学院，河北秦皇岛 066100

通讯作者: 孔健

Abstract

Abstract: A method for identifying the community structure is proposed in this paper based on semi-supervised model.By introducing the Gravity，the communities structure is detected by calculating relationship between the labeled nodes and the unlabeled nodes.The results of experiment prove that the algorithm can identify the community structure in some real-networks.

Key words: complex networks, community structure, semi-supervised classification

摘要： 提出了一种基于半监督模式的复杂网络社团划分新方法，通过引入物理学中的万有引力定理进而计算出有标签节点与周围无标签节点的相互作用值，最终将网络中的社团划分出来。实验表明，算法可以比较准确地划分出一些网络中的社团结构。

关键词: 复杂网络, 社团结构, 半监督分类

CLC Number:

TP393

KONG Jian1，XIE Fuding1，SUN Yan1，ZHAO Fengxia2. Classification method in complex networks based on Semi-supervising[J]. Computer Engineering and Applications, 2011, 47(4): 47-49.

孔健¹，谢福鼎¹，孙岩¹，赵凤霞². 半监督模式下复杂网络分类的方法[J]. 计算机工程与应用, 2011, 47(4): 47-49.

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Classification method in complex networks based on Semi-supervising

半监督模式下复杂网络分类的方法

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