Multi-objective evolutionary clustering with complex networks
作者：
Highlights：
• A Novel multi-objective clustering algorithm based on complex networks was proposed.
• This algorithm can automatically determine the optimal number of clusters.
• Centrality-based initial population was proposed for improving the convergence rate.
• Modularity-based operators were introduced for increasing algorithm's performance.
• Experiments show the effectiveness of our algorithm which outperforms the others.
摘要
•A Novel multi-objective clustering algorithm based on complex networks was proposed.•This algorithm can automatically determine the optimal number of clusters.•Centrality-based initial population was proposed for improving the convergence rate.•Modularity-based operators were introduced for increasing algorithm's performance.•Experiments show the effectiveness of our algorithm which outperforms the others.
论文关键词：Complex networks,Multi-objective evolutionary clustering,Node centrality,Modularity
论文评审过程：Received 25 June 2019, Revised 13 August 2020, Accepted 22 August 2020, Available online 31 August 2020, Version of Record 16 September 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113916
