Application of Overlapping Community Discovery Algorithm in Complex Network Big Data

This paper first introduced the complex network and community discovery and then designed an improved community overlap propagation algorithm (COPRA) algorithm based on the labeling algorithm, i.e., improving the performance of the algorithm by reducing the initial labels and updating asynchronously...

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Bibliographic Details
Published in:Automatic control and computer sciences 2021-12, Vol.55 (Suppl 1), p.8-15
Main Author: Cao, Jiqing
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Computer Science
Control Structures and Microprogramming
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Summary:This paper first introduced the complex network and community discovery and then designed an improved community overlap propagation algorithm (COPRA) algorithm based on the labeling algorithm, i.e., improving the performance of the algorithm by reducing the initial labels and updating asynchronously. The results demonstrated that the algorithm designed in this study could also find overlapping communities when the community structure was not obvious, and its EQ value was always larger than other algorithms. The results of real data sets showed that the EQ value of ICOPRA was 62.86, 217, and 67.65% larger than SLPA, CPM, and COPRA, respectively, when Zachary was taken as an example, but the calculation time slightly increased. The experimental results show the effectiveness of the proposed method, which can be further promoted and applied in practice.
ISSN:0146-4116
1558-108X
DOI:10.3103/S0146411621090042