Network community partition based on intelligent clustering algorithm
Автор: Cai Zhongmin
Журнал: Компьютерная оптика @computer-optics
Рубрика: Численные методы и анализ данных
Статья в выпуске: 6 т.44, 2020 года.
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The division of network community is an important part of network research. Based on the clustering algorithm, this study analyzed the partition method of network community. Firstly, the classic Louvain clustering algorithm was introduced, and then it was improved based on the node similarity to get better partition results. Finally, experiments were carried out on the random network and the real network. The results showed that the improved clustering algorithm was faster than GN and KL algorithms, the community had larger modularity, and the purity was closer to 1. The experimental results show the effectiveness of the proposed method and make some contributions to the reliable community division.
Clustering algorithm, network community, node similarity, community division
Короткий адрес: https://sciup.org/140250075
IDR: 140250075 | DOI: 10.18287/2412-6179-CO-724
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