Community detection in multiplex networks via consensus matrix

In complex network of real world,there are many types of relationships between individuals,and the more effective research ways for this kind of network is to abstract these relationship as a multiplex network.More and more researchers are attracted to be engaged in multiplex network research.A nove...

Full description

Saved in:
Bibliographic Details
Main Authors: Nianwen Ning, Bin Wu
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2017-09-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00199
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1841530215651606528
author Nianwen Ning
Bin Wu
author_facet Nianwen Ning
Bin Wu
author_sort Nianwen Ning
collection DOAJ
description In complex network of real world,there are many types of relationships between individuals,and the more effective research ways for this kind of network is to abstract these relationship as a multiplex network.More and more researchers are attracted to be engaged in multiplex network research.A novel framework of community detection of multiplex network based on consensus matrix was presented.Firstly,this framework merges the structure of multiplex network and the information of link between each node into monoplex network.Then,the community structure information of each layer network was obtained through consensus matrix,and the traditional community division algorithm was utilized to carry out community detection of combine networks.The experimental results show that the proposed algorithm can get better performance of community partition in the real network datasets.
format Article
id doaj-art-6e098f5c6a5f4346aa4b30e7266aa127
institution Kabale University
issn 2096-109X
language English
publishDate 2017-09-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-6e098f5c6a5f4346aa4b30e7266aa1272025-01-15T03:06:05ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2017-09-013677759551532Community detection in multiplex networks via consensus matrixNianwen NingBin WuIn complex network of real world,there are many types of relationships between individuals,and the more effective research ways for this kind of network is to abstract these relationship as a multiplex network.More and more researchers are attracted to be engaged in multiplex network research.A novel framework of community detection of multiplex network based on consensus matrix was presented.Firstly,this framework merges the structure of multiplex network and the information of link between each node into monoplex network.Then,the community structure information of each layer network was obtained through consensus matrix,and the traditional community division algorithm was utilized to carry out community detection of combine networks.The experimental results show that the proposed algorithm can get better performance of community partition in the real network datasets.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00199multiplex networkcommunity detectionconsensus matrix
spellingShingle Nianwen Ning
Bin Wu
Community detection in multiplex networks via consensus matrix
网络与信息安全学报
multiplex network
community detection
consensus matrix
title Community detection in multiplex networks via consensus matrix
title_full Community detection in multiplex networks via consensus matrix
title_fullStr Community detection in multiplex networks via consensus matrix
title_full_unstemmed Community detection in multiplex networks via consensus matrix
title_short Community detection in multiplex networks via consensus matrix
title_sort community detection in multiplex networks via consensus matrix
topic multiplex network
community detection
consensus matrix
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00199
work_keys_str_mv AT nianwenning communitydetectioninmultiplexnetworksviaconsensusmatrix
AT binwu communitydetectioninmultiplexnetworksviaconsensusmatrix