10 citations · 11 across the 2 of their papers we have counts for
3 papers
cs.IR2022★ 1 cited
Neural Re-ranking in Multi-stage Recommender Systems: A Review
Weiwen Liu, Yunjia Xi, Jiarui Qin +5
As the final stage of the multi-stage recommender system (MRS), re-ranking directly affects user experience and satisfaction by rearranging the input ranking lists, and thereby pla…
cs.SI2021★ 10 cited
Extracting Attentive Social Temporal Excitation for Sequential Recommendation
Yunzhe Li, Yue Ding, Bo Chen +5
In collaborative filtering, it is an important way to make full use of social information to improve the recommendation quality, which has been proved to be effective because user…
cs.IR2020
An Embedding Learning Framework for Numerical Features in CTR Prediction
Huifeng Guo, Bo Chen, Ruiming Tang +3
Click-Through Rate (CTR) prediction is critical for industrial recommender systems, where most deep CTR models follow an Embedding \& Feature Interaction paradigm. However, the maj…