17 citations · 48 across the 9 of their papers we have counts for
4 papers · 1 filter
Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation
Jiazheng Jing, Yinan Zhang, Xin Zhou +1
Recommender systems have been gaining increasing research attention over the years. Most existing recommendation methods focus on capturing users' personalized preferences through…
A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions
Hongyu Zhou, Xin Zhou, Zhiwei Zeng +2
Recommendation systems have become popular and effective tools to help users discover their interesting items by modeling the user preference and item property based on implicit in…
Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation
Hongyu Zhou, Xin Zhou, Lingzi Zhang +1
User interaction data in recommender systems is a form of dyadic relation that reflects the preferences of users with items. Learning the representations of these two discrete sets…
Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack Perspective
Yongwei Wang, Yong Liu, Zhiqi Shen
Graph neural networks (GNN) based collaborative filtering (CF) have attracted increasing attention in e-commerce and social media platforms. However, there still lack efforts to ev…