14 citations · 34 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
ICPE: An Item Cluster-Wise Pareto-Efficient Framework for Recommendation Debiasing
Yule Wang, Xin Xin, Yue Ding +2
Recommender system based on historical user-item interactions is of vital importance for web-based services. However, the observed data used to train the recommender model suffers…
DemiNet: Dependency-Aware Multi-Interest Network with Self-Supervised Graph Learning for Click-Through Rate Prediction
Yule Wang, Qiang Luo, Yue Ding +3
In this paper, we propose a novel model named DemiNet (short for DEpendency-Aware Multi-Interest Network) to address the above two issues. To be specific, we first consider various…
Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation
Zhe Xie, Chengxuan Liu, Yichi Zhang +3
Sequential recommendation as an emerging topic has attracted increasing attention due to its important practical significance. Models based on deep learning and attention mechanism…