Comment recommendation based on graph bidirectional aggregation networks

作者：

Highlights：

• A graph bidirectional aggregation network is proposed for strengthening node representation capabilities.

• Use multi-task learning to fuse node embedding and link prediction models.

• Alleviate the impact of online trolls on the daily life of netizens based on the proposed method.

摘要

•A graph bidirectional aggregation network is proposed for strengthening node representation capabilities.•Use multi-task learning to fuse node embedding and link prediction models.•Alleviate the impact of online trolls on the daily life of netizens based on the proposed method.

论文关键词：Recommender systems,Graph neural network,Online comments,Node embedding,Link prediction

论文评审过程：Received 26 April 2022, Revised 24 July 2022, Accepted 8 August 2022, Available online 13 August 2022, Version of Record 20 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118506