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LPA-MNI: An Improved Label Propagation Algorithm Based on Modularity and Node Importance for Community Detection
| Content Provider | MDPI |
|---|---|
| Author | Li, Huan Zhang, Ruisheng Zhao, Zhili Liu, Xin |
| Copyright Year | 2021 |
| 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. |
| Starting Page | 497 |
| e-ISSN | 10994300 |
| DOI | 10.3390/e23050497 |
| Journal | Entropy |
| Issue Number | 5 |
| Volume Number | 23 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-04-21 |
| Access Restriction | Open |
| Subject Keyword | Entropy Industrial Engineering Community Detection Randomness Label Propagation Modularity Node Importance |
| Content Type | Text |
| Resource Type | Article |
