10 citations · 16 across the 8 of their papers we have counts for
8 papers
FedMM: Federated Collaborative Signal Quantization for Multi-Market CTR Prediction
Jun Zhang, Dugang Liu, Xing Tang +2
Online platforms such as Amazon and Netflix serve users across multiple countries and regions, underscoring the importance of multi-market recommendation (MMR). Most MMR methods ad…
Sample Enrichment via Temporary Operations on Subsequences for Sequential Recommendation
Shu Chen, Jinwei Luo, Weike Pan +3
Sequential recommendation leverages interaction sequences to predict forthcoming user behaviors, crucial for crafting personalized recommendations. However, the true preferences of…
BMLP: Behavior-aware MLP for Heterogeneous Sequential Recommendation
Weixin Li, Yuhao Wu, Yang Liu +2
In real recommendation scenarios, users often have different types of behaviors, such as clicking and buying. Existing research methods show that it is possible to capture the hete…
Privacy-Preserving Cross-Domain Sequential Recommendation
Zhaohao Lin, Weike Pan, Zhong Ming
Cross-domain sequential recommendation is an important development direction of recommender systems. It combines the characteristics of sequential recommender systems and cross-dom…
A Survey on Cross-Domain Sequential Recommendation
Shu Chen, Zitao Xu, Weike Pan +2
Cross-domain sequential recommendation (CDSR) shifts the modeling of user preferences from flat to stereoscopic by integrating and learning interaction information from multiple do…
A Survey on Multi-Behavior Sequential Recommendation
Xiaoqing Chen, Zhitao Li, Weike Pan +1
Recommender systems is set up to address the issue of information overload in traditional information retrieval systems, which is focused on recommending information that is of mos…
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation
Dugang Liu, Yang Qiao, Xing Tang +4
Research on debiased recommendation has shown promising results. However, some issues still need to be handled for its application in industrial recommendation. For example, most o…
PAS: A Position-Aware Similarity Measurement for Sequential Recommendation
Zijie Zeng, Jing Lin, Weike Pan +2
The common item-based collaborative filtering framework becomes a typical recommendation method when equipped with a certain item-to-item similarity measurement. On one hand, we re…