activity
20222024
most citedSequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities

64 citations · 65 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2024

Edge Classification on Graphs: New Directions in Topological Imbalance

Xueqi Cheng, Yu Wang, Yunchao Liu +3

Recent years have witnessed the remarkable success of applying Graph machine learning (GML) to node/graph classification and link prediction. However, edge classification task that…

cs.LG2024

Precedence-Constrained Winter Value for Effective Graph Data Valuation

Hongliang Chi, Wei Jin, Charu Aggarwal +1

Data valuation is essential for quantifying data's worth, aiding in assessing data quality and determining fair compensation. While existing data valuation methods have proven effe…

cs.IR2024

Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation

Yuying Zhao, Yu Wang, Yi Zhang +3

Online dating platforms have gained widespread popularity as a means for individuals to seek potential romantic relationships. While recommender systems have been designed to impro…

cs.LG20231 cited

Distance-Based Propagation for Efficient Knowledge Graph Reasoning

Harry Shomer, Yao Ma, Juanhui Li +3

Knowledge graph completion (KGC) aims to predict unseen edges in knowledge graphs (KGs), resulting in the discovery of new facts. A new class of methods have been proposed to tackl…

cs.IR2023

Fairness and Diversity in Recommender Systems: A Survey

Yuying Zhao, Yu Wang, Yunchao Liu +3

Recommender systems are effective tools for mitigating information overload and have seen extensive applications across various domains. However, the single focus on utility goals…

cs.IR202264 cited

Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities

Shoujin Wang, Qi Zhang, Liang Hu +3

In recent years, sequential recommender systems (SRSs) and session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs to capture users' short-term but dynamic…