BiInfGCN: Bilateral Information Augmentation of Graph Convolutional Networks for Recommendation

BiInfGCN: Bilateral Information Augmentation of Graph Convolutional Networks for Recommendation

The current graph-neural-network-based recommendation algorithm fully considers the interaction between users and items. It achieves better recommendation results, but due to a large amount of data, the interaction between users and items still suffers from the problem of data sparsity. To address t...

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Bibliographic Details
Main Authors: Jingfeng Guo, Chao Zheng, Shanshan Li, Yutong Jia, Bin Liu
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Mathematics
Subjects:
recommended system
graphical convolutional neural networks
deep learning
knowledge distillation
personalized recommendations
Online Access:https://www.mdpi.com/2227-7390/10/17/3042

Internet

https://www.mdpi.com/2227-7390/10/17/3042

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