Diffusion network embedding
作者：
Highlights：
• The network diffusion based embedding method solves the limitations of random walks.
• Diffusion driven process is employed to capture both depth and breadth information.
• The time dimension attached to node sequences strengthens information preserving.
• The network inference technique based on cascades captures the global information.
• Our method is more robust to low sampling frequency and highly unbalanced networks.
摘要
•The network diffusion based embedding method solves the limitations of random walks.•Diffusion driven process is employed to capture both depth and breadth information.•The time dimension attached to node sequences strengthens information preserving.•The network inference technique based on cascades captures the global information.•Our method is more robust to low sampling frequency and highly unbalanced networks.
论文关键词：Network embedding,Cascades,Diffusion process,Network inference,Dimension reduction
论文评审过程：Received 11 July 2018, Revised 1 November 2018, Accepted 6 December 2018, Available online 11 December 2018, Version of Record 15 December 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2018.12.004
