13 citations · 29 across the 38 of their papers we have counts for
4 papers · 1 filter
Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection
Yuanchen Bei, Sheng Zhou, Qiaoyu Tan +4
Unsupervised graph anomaly detection is crucial for various practical applications as it aims to identify anomalies in a graph that exhibit rare patterns deviating significantly fr…
Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering
Yijie Zhang, Yuanchen Bei, Shiqi Yang +4
Graph collaborative filtering, which learns user and item representations through message propagation over the user-item interaction graph, has been shown to effectively enhance re…
Modeling Spatiotemporal Periodicity and Collaborative Signal for Local-Life Service Recommendation
Huixuan Chi, Hao Xu, Mengya Liu +4
Online local-life service platforms provide services like nearby daily essentials and food delivery for hundreds of millions of users. Different from other types of recommender sys…
CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks
Yuanchen Bei, Hao Xu, Sheng Zhou +5
Dynamic graph data mining has gained popularity in recent years due to the rich information contained in dynamic graphs and their widespread use in the real world. Despite the adva…