12 citations · 18 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
A Text-based Deep Reinforcement Learning Framework for Interactive Recommendation
Chaoyang Wang, Zhiqiang Guo, Jianjun Li +2
Due to its nature of learning from dynamic interactions and planning for long-run performance, reinforcement learning (RL) recently has received much attention in interactive recom…