59 citations · 138 across the 6 of their papers we have counts for
6 papers
Lightweight yet Efficient: An External Attentive Graph Convolutional Network with Positional Prompts for Sequential Recommendation
Jinyu Zhang, Chao Li, Zhongying Zhao
Graph-based Sequential Recommender systems (GSRs) have gained significant research attention due to their ability to simultaneously handle user-item interactions and sequential rel…
Lightweight yet Fine-grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-account Sequential Recommendation
Jinyu Zhang, Zhongying Zhao, Chao Li +1
Shared-account Sequential Recommendation (SSR) aims to provide personalized recommendations for accounts shared by multiple users with varying sequential preferences. Previous stud…
Unbiased and Robust: External Attention-enhanced Graph Contrastive Learning for Cross-domain Sequential Recommendation
Xinhua Wang, Houping Yue, Zizheng Wang +2
Cross-domain sequential recommenders (CSRs) are gaining considerable research attention as they can capture user sequential preference by leveraging side information from multiple…
Towards Lightweight Cross-domain Sequential Recommendation via External Attention-enhanced Graph Convolution Network
Jinyu Zhang, Huichuan Duan, Lei Guo +2
Cross-domain Sequential Recommendation (CSR) is an emerging yet challenging task that depicts the evolution of behavior patterns for overlapped users by modeling their interactions…
Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation
Lei Guo, Jinyu Zhang, Tong Chen +2
Shared-account Cross-domain Sequential Recommendation (SCSR) is an emerging yet challenging task that simultaneously considers the shared-account and cross-domain characteristics i…
Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation
Lei Guo, Jinyu Zhang, Li Tang +3
Shared-account Cross-domain Sequential Recommendation (SCSR) task aims to recommend the next item via leveraging the mixed user behaviors in multiple domains. It is gaining immense…