430 citations · 981 across the 16 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.IR2018★ 430 cited
Deep Reinforcement Learning for Page-wise Recommendations
Xiangyu Zhao, Long Xia, Liang Zhang +3
Recommender systems can mitigate the information overload problem by suggesting users' personalized items. In real-world recommendations such as e-commerce, a typical interaction b…
cs.IR2018★ 401 cited
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
Xiangyu Zhao, Liang Zhang, Zhuoye Ding +3
Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional reco…
cs.LG2018★ 107 cited
Deep Reinforcement Learning for List-wise Recommendations
Xiangyu Zhao, Liang Zhang, Long Xia +3
Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional reco…