Dynamic network embedding via structural attention
作者：
Highlights：
• We propose a novel dynamic network embedding model with structural attention.
• Our model can capture the evolving characteristic of dynamic networks.
• The proposed method models the process of developing an open triad into a closed triad.
• The learned representations can preserve both the first-order and second-order proximities.
• The experimental results demonstrate the efficiency of our method.
摘要
•We propose a novel dynamic network embedding model with structural attention.•Our model can capture the evolving characteristic of dynamic networks.•The proposed method models the process of developing an open triad into a closed triad.•The learned representations can preserve both the first-order and second-order proximities.•The experimental results demonstrate the efficiency of our method.
论文关键词：Dynamic network,Attention mechanism,Network embedding
论文评审过程：Received 12 November 2019, Revised 27 January 2021, Accepted 6 March 2021, Available online 16 March 2021, Version of Record 7 April 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114895
