A Simple Graph Convolutional Network With Abundant Interaction for Collaborative Filtering

Recently, recommender systems based on Graph Convolution Network (GCN) have become a research hotspot, especially in collaborative filtering. However, most GCN-based models have inferior embedding propagation mechanism, leading to low information extraction efficiency. Besides, the existing methods...

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Главные авторы:	Ronghui Guo, Xunkai Li, Youpeng Hu, Yixuan Wu, Xin Xiong, Meixia Qu
Формат:	Artigo
Язык:	Inglês
Опубликовано:	IEEE 2021-01-01
Серии:	IEEE Access
Предметы:	Collaborative filtering graph convolutional network recommender systems
Online-ссылка:	https://ieeexplore.ieee.org/document/9440428/
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