36 citations · 66 across the 5 of their papers we have counts for
5 papers
SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
Chi Zhang, Qilong Han, Rui Chen +3
Traditional sequential recommendation methods assume that users' sequence data is clean enough to learn accurate sequence representations to reflect user preferences. In practice,…
Adaptive Hardness Negative Sampling for Collaborative Filtering
Riwei Lai, Rui Chen, Qilong Han +2
Negative sampling is essential for implicit collaborative filtering to provide proper negative training signals so as to achieve desirable performance. We experimentally unveil a c…
Augmented Negative Sampling for Collaborative Filtering
Yuhan Zhao, Rui Chen, Riwei Lai +3
Negative sampling is essential for implicit-feedback-based collaborative filtering, which is used to constitute negative signals from massive unlabeled data to guide supervised lea…
Trajectory Data Collection with Local Differential Privacy
Yuemin Zhang, Qingqing Ye, Rui Chen +2
Trajectory data collection is a common task with many applications in our daily lives. Analyzing trajectory data enables service providers to enhance their services, which ultimate…
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
Chi Zhang, Rui Chen, Xiangyu Zhao +2
In practical recommendation scenarios, users often interact with items under multi-typed behaviors (e.g., click, add-to-cart, and purchase). Traditional collaborative filtering tec…