36 citations · 61 across the 9 of their papers we have counts for
4 papers · 1 filter
Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction
Xiang Xu, Hao Wang, Wei Guo +6
Click-through Rate (CTR) prediction is crucial for online personalization platforms. Recent advancements have shown that modeling rich user behaviors can significantly improve the…
Denoising Pre-Training and Customized Prompt Learning for Efficient Multi-Behavior Sequential Recommendation
Hao Wang, Yongqiang Han, Kefan Wang +6
In the realm of recommendation systems, users exhibit a diverse array of behaviors when interacting with items. This phenomenon has spurred research into learning the implicit sema…
Dataset Regeneration for Sequential Recommendation
Mingjia Yin, Hao Wang, Wei Guo +5
The sequential recommender (SR) system is a crucial component of modern recommender systems, as it aims to capture the evolving preferences of users. Significant efforts have been…
END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation
Yongqiang Han, Hao Wang, Kefan Wang +6
In recommendation systems, users frequently engage in multiple types of behaviors, such as clicking, adding to a cart, and purchasing. However, with diversified behavior data, user…