Jian Liang

Meta Graph Learning for Long-tail Recommendation

2023

Highly skewed long-tail item distribution commonly hurts model performance on tail items in recommendation systems, especially for graph-based recommendation models. We propose a novel idea to learn relations among items as an auxiliary graph to …

LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

Contemporary recommendation systems predominantly rely on ID embedding to capture latent associations among users and items. However, this approach overlooks the wealth of semantic information embedded within textual descriptions of items, leading to suboptimal performance …