LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection
Community detection is of great significance in understanding the structure of the network. Label propagation algorithm (LPA) is a classical and effective method, but it has the problems of randomness and instability. An improved label propagation algorithm named LPA-MNI is proposed in this study by...
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doaj-48012c635b684c2fa078afd54eaa88502021-04-21T23:08:16ZengMDPI AGEntropy1099-43002021-04-012349749710.3390/e23050497LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community DetectionHuan Li0Ruisheng Zhang1Zhili Zhao2Xin Liu3School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, ChinaSchool of Information Science and Engineering, Lanzhou University, Lanzhou 730000, ChinaSchool of Information Science and Engineering, Lanzhou University, Lanzhou 730000, ChinaSchool of Information Science and Engineering, Lanzhou University, Lanzhou 730000, ChinaCommunity detection is of great significance in understanding the structure of the network. Label propagation algorithm (LPA) is a classical and effective method, but it has the problems of randomness and instability. An improved label propagation algorithm named LPA-MNI is proposed in this study by combining the modularity function and node importance with the original LPA. LPA-MNI first identify the initial communities according to the value of modularity. Subsequently, the label propagation is used to cluster the remaining nodes that have not been assigned to initial communities. Meanwhile, node importance is used to improve the node order of label updating and the mechanism of label selecting when multiple labels are contained by the maximum number of nodes. Extensive experiments are performed on twelve real-world networks and eight groups of synthetic networks, and the results show that LPA-MNI has better accuracy, higher modularity, and more reasonable community numbers when compared with other six algorithms. In addition, LPA-MNI is shown to be more robust than the traditional LPA algorithm.https://www.mdpi.com/1099-4300/23/5/497community detectionrandomnesslabel propagationmodularitynode importance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Huan Li Ruisheng Zhang Zhili Zhao Xin Liu |
spellingShingle |
Huan Li Ruisheng Zhang Zhili Zhao Xin Liu LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection Entropy community detection randomness label propagation modularity node importance |
author_facet |
Huan Li Ruisheng Zhang Zhili Zhao Xin Liu |
author_sort |
Huan Li |
title |
LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection |
title_short |
LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection |
title_full |
LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection |
title_fullStr |
LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection |
title_full_unstemmed |
LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection |
title_sort |
lpa-mni: an improved label propagation algorithm based on modularity and node importance for community detection |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2021-04-01 |
description |
Community detection is of great significance in understanding the structure of the network. Label propagation algorithm (LPA) is a classical and effective method, but it has the problems of randomness and instability. An improved label propagation algorithm named LPA-MNI is proposed in this study by combining the modularity function and node importance with the original LPA. LPA-MNI first identify the initial communities according to the value of modularity. Subsequently, the label propagation is used to cluster the remaining nodes that have not been assigned to initial communities. Meanwhile, node importance is used to improve the node order of label updating and the mechanism of label selecting when multiple labels are contained by the maximum number of nodes. Extensive experiments are performed on twelve real-world networks and eight groups of synthetic networks, and the results show that LPA-MNI has better accuracy, higher modularity, and more reasonable community numbers when compared with other six algorithms. In addition, LPA-MNI is shown to be more robust than the traditional LPA algorithm. |
topic |
community detection randomness label propagation modularity node importance |
url |
https://www.mdpi.com/1099-4300/23/5/497 |
work_keys_str_mv |
AT huanli lpamnianimprovedlabelpropagationalgorithmbasedonmodularityandnodeimportanceforcommunitydetection AT ruishengzhang lpamnianimprovedlabelpropagationalgorithmbasedonmodularityandnodeimportanceforcommunitydetection AT zhilizhao lpamnianimprovedlabelpropagationalgorithmbasedonmodularityandnodeimportanceforcommunitydetection AT xinliu lpamnianimprovedlabelpropagationalgorithmbasedonmodularityandnodeimportanceforcommunitydetection |
_version_ |
1721515210834968576 |