Learning ladder neural networks for semi-supervised node classification in social network

作者：

Highlights：

• Propose a novel semi-supervised node classification method with ladder neural network.

• The model is a SSNC-oriented node embedding method in framework of deep learning.

• The method could effectively utilize unsupervised learning to improve the performance.

• Experimental results demonstrate the superiority and effectiveness of the method.

摘要

•Propose a novel semi-supervised node classification method with ladder neural network.•The model is a SSNC-oriented node embedding method in framework of deep learning.•The method could effectively utilize unsupervised learning to improve the performance.•Experimental results demonstrate the superiority and effectiveness of the method.

论文关键词：Semi-supervised node classification,Graph convolutional network,Ladder neural networks,Network embedding

论文评审过程：Received 8 April 2020, Revised 18 August 2020, Accepted 31 August 2020, Available online 3 September 2020, Version of Record 7 September 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113957