4 citations · 6 across the 3 of their papers we have counts for
4 papers
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…
Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation
Huixuan Chi, Hao Xu, Hao Fu +5
Modeling the evolution of user preference is essential in recommender systems. Recently, dynamic graph-based methods have been studied and achieved SOTA for recommendation, majorit…
Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks
Huixuan Chi, Yuying Wang, Qinfen Hao +1
Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks. In the literature, however, most tric…