Graph contrast learning for recommendation based on relational graph convolutional neural network

Current knowledge graph-based recommendation methods heavily rely on high-quality knowledge graphs, often falling short in effectively addressing issues such as the cold start problem and heterogeneous noise in user interactions. This leads to biases in user interest and popularity. To overcome thes...

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Hlavní autoři:	Xiaoyang Liu, Hanwen Feng, Xiaoqin Zhang, Xia Zhou, Asgarali Bouyer
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2024-10-01
Edice:	Journal of King Saud University: Computer and Information Sciences
Témata:	Recommendation system Graph convolutional neural network Graph contrast learning Knowledge graph
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S131915782400257X
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