DBSCAN算法在电子邮件网络社团发现中的应用

doi:10.11896/j.issn.1002-137X.2017.6A.133

计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 591-593.doi: 10.11896/j.issn.1002-137X.2017.6A.133

DBSCAN算法在电子邮件网络社团发现中的应用

杨芳勋

四川九洲集团中央研究院成都610041

出版日期:2017-12-01 发布日期:2018-12-01

Application of DBSCAN Algorithm in Electronic Mail Network Community Detection

YANG Fang-xun

Online:2017-12-01 Published:2018-12-01

摘要/Abstract

摘要： 针对电子邮件复杂网络中的社团发现问题,将具有良好聚类性能的DBSCAN算法引入电子邮件网络社团发现。基于对该算法的分析,研究了电子邮件网络社团发现的系统架构及算法实现流程。最后通过对安然邮件语料集的测试验证了DBSCAN算法在社团发现中的可行性。

关键词: 电子邮件网络,社团发现,DBSCAN算法

Abstract: According to the community detection in the email complex network,the DBSCAN algorithm was introduced into the email network to detect the community in this paper.Based on the analysis of the algorithm,the system architecture and algorithm implementation process of email network community detection were studied.Finally,the feasibility of the DBSCAN algorithm in electronic mail network community detection was verified by the test of the Enron email corpus.

Key words: Electronic mail network,Community detection,DBSCAN algorithm

杨芳勋. DBSCAN算法在电子邮件网络社团发现中的应用[J]. 计算机科学, 2017, 44(Z6): 591-593. https://doi.org/10.11896/j.issn.1002-137X.2017.6A.133

YANG Fang-xun. Application of DBSCAN Algorithm in Electronic Mail Network Community Detection[J]. Computer Science, 2017, 44(Z6): 591-593. https://doi.org/10.11896/j.issn.1002-137X.2017.6A.133

参考文献

[1] 杨博,刘大友,金第,等.复杂网络聚类方法[J].软件学报,2009,0(1):54-66.
[2] 罗浪,张绍武,陈韬.基于稠密子团和边聚类系数的局部社团挖掘算法[J].电子设计工程,2013,1(18):36-40.
[3] NEWMAN M E J.Detecting community structure in networks [J].European Physical Journal,2004,8(2):321-330.
[4] 林旺群,卢风顺,丁兆云,等.基于带权图的层次化社团并行计算方法[J].软件学报,2012,3(6):1517-1530.
[5] 马菲,徐汀荣.基于种子边的重叠社团发现算法[J].计算机应用研究,2015,2(9):2563-2596.

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DBSCAN算法在电子邮件网络社团发现中的应用

Application of DBSCAN Algorithm in Electronic Mail Network Community Detection

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