2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.IR2024★ 1 cited
iVAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
Xuying Ning, Wujiang Xu, Tianxin Wei +1
Cross-Domain Sequential Recommendation (CDSR) leverages user behaviors across multiple domains to mitigate data sparsity and cold-start challenges in Single-Domain Sequential Recom…
cs.IR2023★ 2 cited
Neural Node Matching for Multi-Target Cross Domain Recommendation
Wujiang Xu, Shaoshuai Li, Mingming Ha +5
Multi-Target Cross Domain Recommendation(CDR) has attracted a surge of interest recently, which intends to improve the recommendation performance in multiple domains (or systems) s…
cs.LG2022
Semi-Supervised Heterogeneous Graph Learning with Multi-level Data Augmentation
Ying Chen, Siwei Qiang, Mingming Ha +5
In recent years, semi-supervised graph learning with data augmentation (DA) is currently the most commonly used and best-performing method to enhance model robustness in sparse sce…