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cs.IR2024★ 1 cited
Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph
Qian Zhao, Hao Qian, Ziqi Liu +2
Recommendation systems are widely used in e-commerce websites and online platforms to address information overload. However, existing systems primarily rely on historical data and…
cs.IR2023
Long-tail Augmented Graph Contrastive Learning for Recommendation
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang +1
Graph Convolutional Networks (GCNs) has demonstrated promising results for recommender systems, as they can effectively leverage high-order relationship. However, these methods usu…