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Found 4 papers, 1 papers with code
Modeling Spatiotemporal Periodicity and Collaborative Signal for Local-Life Service Recommendation
(2) spatiotemporal collaborative signal, which indicates similar users have similar preferences at specific locations and times.
CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks
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.
Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation
In particular: 1) existing methods do not explicitly encode and capture the evolution of short-term preference as sequential methods do; 2) simply using last few interactions is not enough for modeling the changing trend.
Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks
Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks.
Ranked #22 on
Node Property Prediction
on ogbn-mag
