110 citations · 229 across the 5 of their papers we have counts for
5 papers
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…
Deep Spatially and Temporally Aware Similarity Computation for Road Network Constrained Trajectories
Ziquan Fang, Yuntao Du, Xinjun Zhu +3
Trajectory similarity computation has drawn massive attention, as it is core functionality in a wide range of applications such as ride-sharing, traffic analysis, and social recomm…