|Table of Contents|

Social network clustering analysis based on structural approximation

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2020年02期
Page:
230-235
Research Field:
Publishing date:

Info

Title:
Social network clustering analysis based on structural approximation
Author(s):
Wang Yunye1Kong Shan1Li Yalun2
1.College of Information Science & Technology,Zhengzhou Normal University,Zhengzhou 450044,China; 2.School of Electronic and Information Engineering,Tianjin Polytechnic University,Tianjin 300387,China
Keywords:
social network directed graphs network clustering structural approximation
PACS:
TP18
DOI:
10.14177/j.cnki.32-1397n.2020.44.02.015
Abstract:
In view of that the clustering algorithm based on structural approximation can not solve the clustering problem of the asymmetric network,a directed clustering algorithm based on structural approximation is proposed here. The social network is studied as a graph structure,and the network clustering problem is regarded as a sub-graph division to realize the clustering of directed graphs with low complexity. The algorithm was achieved by C++programming,and the customized directed network datasets and standard datasets are used to test the proposed algorithm. The experimental results show that the algorithm for the network structure is more accurate and can identify the outliers and hub points.

References:

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Last Update: 2020-04-20