69 citations · 69 across the 1 of their papers we have counts for
2 papers
cs.IR2022★ 69 cited
Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
Minghao Zhao, Le Wu, Yile Liang +7
Recent years have witnessed the great accuracy performance of graph-based Collaborative Filtering (CF) models for recommender systems. By taking the user-item interaction behavior…
cs.IR2019
Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks
Tieyun Qian, Yile Liang, Qing Li
Matrix completion is a classic problem underlying recommender systems. It is traditionally tackled with matrix factorization. Recently, deep learning based methods, especially grap…