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SA-SOM algorithm for detecting communities in complex networks

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成果类型:
期刊论文
作者:
Chen, Luogeng;Wang, Yanran;Huang, Xiaoming;Hu, Mengyu;Hu, Fang*
通讯作者:
Hu, Fang
作者机构:
[Hu, Fang; Wang, Yanran; Huang, Xiaoming; Chen, Luogeng; Hu, Mengyu] Hubei Univ Chinese Med, Coll Informat Engn, Wuhan 430065, Hubei, Peoples R China.
[Hu, Fang] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
通讯机构:
[Hu, Fang] H
[Hu, Fang] C
Hubei Univ Chinese Med, Coll Informat Engn, Wuhan 430065, Hubei, Peoples R China.
Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Community detection;SA-SOM algorithm;modularity;normalized mutual information;density;simulation test
期刊:
Modern Physics Letters B
ISSN:
0217-9849
年:
2017
卷:
31
期:
29
页码:
1750262
机构署名:
本校为通讯机构
院系归属:
计算机学院
摘要:
Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficien...

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