53 citations · 53 across the 2 of their papers we have counts for
3 papers
cs.IR2022★ 53 cited
MEGCF: Multimodal Entity Graph Collaborative Filtering for Personalized Recommendation
Kang Liu, Feng Xue, Dan Guo +3
In most E-commerce platforms, whether the displayed items trigger the user's interest largely depends on their most eye-catching multimodal content. Consequently, increasing effort…
cs.LG2020
RGCF: Refined Graph Convolution Collaborative Filtering with concise and expressive embedding
Kang Liu, Feng Xue, Richang Hong
Graph Convolution Network (GCN) has attracted significant attention and become the most popular method for learning graph representations. In recent years, many efforts have been f…
cs.IR2018
Deep Item-based Collaborative Filtering for Top-N Recommendation
Feng Xue, Xiangnan He, Xiang Wang +3
Item-based Collaborative Filtering(short for ICF) has been widely adopted in recommender systems in industry, owing to its strength in user interest modeling and ease in online per…