232 citations · 1.4k across the 72 of their papers we have counts for
5 papers · 1 filter
Graph Collaborative Signals Denoising and Augmentation for Recommendation
Ziwei Fan, Ke Xu, Zhang Dong +3
Graph collaborative filtering (GCF) is a popular technique for capturing high-order collaborative signals in recommendation systems. However, GCF's bipartite adjacency matrix, whic…
ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang +4
Since group activities have become very common in daily life, there is an urgent demand for generating recommendations for a group of users, referred to as group recommendation tas…
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…
Deoscillated Graph Collaborative Filtering
Zhiwei Liu, Lin Meng, Fei Jiang +2
Collaborative Filtering (CF) signals are crucial for a Recommender System~(RS) model to learn user and item embeddings. High-order information can alleviate the cold-start issue of…
Spectral Collaborative Filtering
Lei Zheng, Chun-Ta Lu, Fei Jiang +2
Despite the popularity of Collaborative Filtering (CF), CF-based methods are haunted by the \textit{cold-start} problem, which has a significantly negative impact on users' experie…