110 citations · 229 across the 5 of their papers we have counts for
4 papers · 1 filter
Knowledge-refined Denoising Network for Robust Recommendation
Xinjun Zhu, Yuntao Du, Yuren Mao +3
Knowledge graph (KG), which contains rich side information, becomes an essential part to boost the recommendation performance and improve its explainability. However, existing know…
Self-Guided Learning to Denoise for Robust Recommendation
Yunjun Gao, Yuntao Du, Yujia Hu +4
The ubiquity of implicit feedback makes them the default choice to build modern recommender systems. Generally speaking, observed interactions are considered as positive samples, w…
HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
Yuntao Du, Xinjun Zhu, Lu Chen +2
Knowledge graph (KG) plays an increasingly important role to improve the recommendation performance and interpretability. A recent technical trend is to design end-to-end models ba…
MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation
Yuntao Du, Xinjun Zhu, Lu Chen +2
A knowledge graph (KG) consists of a set of interconnected typed entities and their attributes. Recently, KGs are popularly used as the auxiliary information to enable more accurat…