440 citations · 674 across the 38 of their papers we have counts for
7 papers · 1 filter
Faithfully Explainable Recommendation via Neural Logic Reasoning
Yaxin Zhu, Yikun Xian, Zuohui Fu +2
Knowledge graphs (KG) have become increasingly important to endow modern recommender systems with the ability to generate traceable reasoning paths to explain the recommendation pr…
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation
Yikun Xian, Zuohui Fu, Handong Zhao +8
Recent research explores incorporating knowledge graphs (KG) into e-commerce recommender systems, not only to achieve better recommendation performance, but more importantly to gen…
COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce
Zuohui Fu, Yikun Xian, Yaxin Zhu +2
In this work, we present a new dataset for conversational recommendation over knowledge graphs in e-commerce platforms called COOKIE. The dataset is constructed from an Amazon revi…
Fairness-Aware Explainable Recommendation over Knowledge Graphs
Zuohui Fu, Yikun Xian, Ruoyuan Gao +8
There has been growing attention on fairness considerations recently, especially in the context of intelligent decision making systems. Explainable recommendation systems, in parti…
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation
Xin Dong, Jingchao Ni, Wei Cheng +6
Recently, recommender systems have been able to emit substantially improved recommendations by leveraging user-provided reviews. Existing methods typically merge all reviews of a g…
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Yikun Xian, Zuohui Fu, S. Muthukrishnan +2
Recent advances in personalized recommendation have sparked great interest in the exploitation of rich structured information provided by knowledge graphs. Unlike most existing app…