42 citations · 140 across the 11 of their papers we have counts for
Showing cs.IRShow all
3 papers · 1 filter
cs.IR2024★ 35 cited
Intent-aware Recommendation via Disentangled Graph Contrastive Learning
Yuling Wang, Xiao Wang, Xiangzhou Huang +5
Graph neural network (GNN) based recommender systems have become one of the mainstream trends due to the powerful learning ability from user behavior data. Understanding the user i…
cs.IR2023★ 17 cited
M2GNN: Metapath and Multi-interest Aggregated Graph Neural Network for Tag-based Cross-domain Recommendation
Zepeng Huai, Yuji Yang, Mengdi Zhang +3
Cross-domain recommendation (CDR) is an effective way to alleviate the data sparsity problem. Content-based CDR is one of the most promising branches since most kinds of products c…
cs.IR2022★ 4 cited
Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation
Huixuan Chi, Hao Xu, Hao Fu +5
Modeling the evolution of user preference is essential in recommender systems. Recently, dynamic graph-based methods have been studied and achieved SOTA for recommendation, majorit…