4 citations · 4 across the 4 of their papers we have counts for
4 papers
Intent Propagation Contrastive Collaborative Filtering
Haojie Li, Junwei Du, Guanfeng Liu +3
Disentanglement techniques used in collaborative filtering uncover interaction intents between nodes, improving the interpretability of node representations and enhancing recommend…
Frequency-Corrupt Based Graph Self-Supervised Learning
Haojie Li, Mengjiao Zhang, Guanfeng Liu +3
Graph self-supervised learning can reduce the need for labeled graph data and has been widely used in recommendation, social networks, and other web applications. However, existing…
Behavior Pattern Mining-based Multi-Behavior Recommendation
Haojie Li, Zhiyong Cheng, Xu Yu +3
Multi-behavior recommendation systems enhance effectiveness by leveraging auxiliary behaviors (such as page views and favorites) to address the limitations of traditional models th…
Amplify Graph Learning for Recommendation via Sparsity Completion
Peng Yuan, Haojie Li, Minying Fang +3
Graph learning models have been widely deployed in collaborative filtering (CF) based recommendation systems. Due to the issue of data sparsity, the graph structure of the original…