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cs.IR2024
Understanding Before Recommendation: Semantic Aspect-Aware Review Exploitation via Large Language Models
Fan Liu, Yaqi Liu, Huilin Chen +3
Recommendation systems harness user-item interactions like clicks and reviews to learn their representations. Previous studies improve recommendation accuracy and interpretability…
cs.IR2024
Cluster-based Graph Collaborative Filtering
Fan Liu, Shuai Zhao, Zhiyong Cheng +2
Graph Convolution Networks (GCNs) have significantly succeeded in learning user and item representations for recommendation systems. The core of their efficacy is the ability to ex…
cs.IR2024
Attribute-driven Disentangled Representation Learning for Multimodal Recommendation
Zhenyang Li, Fan Liu, Yinwei Wei +3
Recommendation algorithms forecast user preferences by correlating user and item representations derived from historical interaction patterns. In pursuit of enhanced performance, m…