A Node Influence Based Label Propagation Algorithm for Community Detection in Networks

A Node Influence Based Label Propagation Algorithm for Community Detection in Networks

Label propagation algorithm (LPA) is an extremely fast community detection method and is widely used in large scale networks. In spite of the advantages of LPA, the issue of its poor stability has not yet been well addressed. We propose a novel node influence based label propagation algorithm for co...

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Main Authors: Yan Xing, Fanrong Meng, Yong Zhou, Mu Zhu, Mengyu Shi, Guibin Sun
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/627581
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spelling doaj-9769e31f966b4cf7bbf4fcfa9bed0aac2020-11-25T02:24:30ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/627581627581A Node Influence Based Label Propagation Algorithm for Community Detection in NetworksYan Xing0Fanrong Meng1Yong Zhou2Mu Zhu3Mengyu Shi4Guibin Sun5School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, ChinaLabel propagation algorithm (LPA) is an extremely fast community detection method and is widely used in large scale networks. In spite of the advantages of LPA, the issue of its poor stability has not yet been well addressed. We propose a novel node influence based label propagation algorithm for community detection (NIBLPA), which improves the performance of LPA by improving the node orders of label updating and the mechanism of label choosing when more than one label is contained by the maximum number of nodes. NIBLPA can get more stable results than LPA since it avoids the complete randomness of LPA. The experimental results on both synthetic and real networks demonstrate that NIBLPA maintains the efficiency of the traditional LPA algorithm, and, at the same time, it has a superior performance to some representative methods.http://dx.doi.org/10.1155/2014/627581
collection DOAJ
language English
format Article
sources DOAJ
author Yan Xing
Fanrong Meng
Yong Zhou
Mu Zhu
Mengyu Shi
Guibin Sun
spellingShingle Yan Xing
Fanrong Meng
Yong Zhou
Mu Zhu
Mengyu Shi
Guibin Sun
A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
The Scientific World Journal
author_facet Yan Xing
Fanrong Meng
Yong Zhou
Mu Zhu
Mengyu Shi
Guibin Sun
author_sort Yan Xing
title A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
title_short A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
title_full A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
title_fullStr A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
title_full_unstemmed A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
title_sort node influence based label propagation algorithm for community detection in networks
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description Label propagation algorithm (LPA) is an extremely fast community detection method and is widely used in large scale networks. In spite of the advantages of LPA, the issue of its poor stability has not yet been well addressed. We propose a novel node influence based label propagation algorithm for community detection (NIBLPA), which improves the performance of LPA by improving the node orders of label updating and the mechanism of label choosing when more than one label is contained by the maximum number of nodes. NIBLPA can get more stable results than LPA since it avoids the complete randomness of LPA. The experimental results on both synthetic and real networks demonstrate that NIBLPA maintains the efficiency of the traditional LPA algorithm, and, at the same time, it has a superior performance to some representative methods.
url http://dx.doi.org/10.1155/2014/627581
work_keys_str_mv AT yanxing anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT fanrongmeng anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT yongzhou anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT muzhu anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT mengyushi anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT guibinsun anodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT yanxing nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT fanrongmeng nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT yongzhou nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT muzhu nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT mengyushi nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
AT guibinsun nodeinfluencebasedlabelpropagationalgorithmforcommunitydetectioninnetworks
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