2 papers
cs.LG2025
How Do Graph Signals Affect Recommendation: Unveiling the Mystery of Low and High-Frequency Graph Signals
Feng Liu, Hao Cang, Huanhuan Yuan +5
Spectral graph neural networks (GNNs) are highly effective in modeling graph signals, with their success in recommendation often attributed to low-pass filtering. However, recent s…
cs.IR2024
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…