110 citations · 204 across the 8 of their papers we have counts for
8 papers
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…
Maximizing the Influence of Bichromatic Reverse k Nearest Neighbors in Geo-Social Networks
Pengfei Jin, Lu Chen, Yunjun Gao +3
Geo-social networks offer opportunities for the marketing and promotion of geo-located services. In this setting, we explore a new problem, called Maximizing the Influence of Bichr…
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…
CollaborER: A Self-supervised Entity Resolution Framework Using Multi-features Collaboration
Congcong Ge, Pengfei Wang, Lu Chen +3
Entity Resolution (ER) aims to identify whether two tuples refer to the same real-world entity and is well-known to be labor-intensive. It is a prerequisite to anomaly detection, a…
KGClean: An Embedding Powered Knowledge Graph Cleaning Framework
Congcong Ge, Yunjun Gao, Honghui Weng +3
The quality assurance of the knowledge graph is a prerequisite for various knowledge-driven applications. We propose KGClean, a novel cleaning framework powered by knowledge graph…