most citedDistance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.IR2025★ 1 cited

Distance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation

Tao Huang, Yihong Chen, Wei Fan +2

Graph Convolutional Networks (GCNs) are widely used to improve recommendation accuracy and performance by effectively learning the representations of user and item nodes. However,…

cs.IR2024

Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement

Zeyu Hu, Yuzhi Xiao, Tao Huang +1

Sequential recommendation is one of the important branches of recommender system, aiming to achieve personalized recommended items for the future through the analysis and predictio…