12 citations · 15 across the 3 of their papers we have counts for
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cs.IR2024
DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation
Zhiqiang Guo, Guohui Li, Jianjun Li +2
Learning precise representations of users and items to fit observed interaction data is the fundamental task of collaborative filtering. Existing studies usually infer entangled re…
cs.IR2023★ 3 cited
LGMRec: Local and Global Graph Learning for Multimodal Recommendation
Zhiqiang Guo, Jianjun Li, Guohui Li +3
The multimodal recommendation has gradually become the infrastructure of online media platforms, enabling them to provide personalized service to users through a joint modeling of…
cs.IR2020★ 12 cited
A Light Heterogeneous Graph Collaborative Filtering Model using Textual Information
Chaoyang Wang, Zhiqiang Guo, Guohui Li +3
Due to the development of graph neural networks, graph-based representation learning methods have made great progress in recommender systems. However, data sparsity is still a chal…