Article-Journal

Hierarchical Attentive Knowledge Graph Embedding for Personalized Recommendation
Knowledge graphs (KGs) have proven to be effective for high-quality recommendation, where the connectivities between users and items …
Xiao Sha, Zhu Sun, Jie Zhang
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Point-of-Interest Recommendation for Users-Businesses with Uncertain Check-ins
Zhu Sun, Chen Li, Yu Lei, Lu Zhang, Jie Zhang, Shunpan Liang
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Top-aware Recommender Distillation with Deep Reinforcement Learning
Hongyang Liu, Zhu Sun, Xinghua Qu, Fuyong Yuan
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Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy
“Recent studies have revealed that neural network-based policies can be easily fooled by adversarial examples. However, while …
Xinghua Qu, Zhu Sun, Yew Soon Ong, Pengfei Wei, Abhishek Gupta
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Modeling Hierarchical Category Transition for Next POI Recommendation with Uncertain Check-ins
Lu Zhang, Zhu Sun, Jie Zhang, Horst Kloeden, Felix Klanner
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Multi-facet User Preference Learning for Fine-grained Item Recommendation
Guibing Guo, Xin Zhou, Zhu Sun, Yuan Liu
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Research Commentary on Recommendations with Side Information: A Survey and Research Directions
‘Recommender systems have become an essential tool to help resolve the information overload problem in recent decades. …
Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
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BPRH: Bayesian Personalized Ranking for Heterogeneous Implicit Feedback
Yun Liu, Huihuai Qiu, Guibing Guo, Zhu Sun, Jie Zhang, Hai Thanh Nguyen
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