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cs.IR2025
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.IR2025
Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendation
Shutong Qiao, Wei Zhou, Junhao Wen +4
Session-based recommendation (SBR) methods often rely on user behavior data, which can struggle with the sparsity of session data, limiting performance. Researchers have identified…