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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Hlavní autoři:	Jingfeng Guo, Chao Zheng, Shanshan Li, Yutong Jia, Bin Liu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2022-08-01
Edice:	Mathematics
Témata:	recommended system graphical convolutional neural networks deep learning knowledge distillation personalized recommendations
On-line přístup:	https://www.mdpi.com/2227-7390/10/17/3042
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