3 accepted papers
Credit risk assessment has increasingly become a prominent research field due to the dramatically increased incidents of financial default. Traditional graph-based methods have been developed to detect defaulters within user-merchant commercial payment networks. However, these methods face challenge…
Effectively modeling time information and incorporating it into applications or models involving chronologically occurring events is crucial. Real-world scenarios often involve diverse and complex time patterns, which pose significant challenges for time encoding methods. While previous methods focu…
Temporal graph neural networks (TGNNs) have shown remarkable performance in temporal graph modeling. However, real-world temporal graphs often possess rich textual information, giving rise to temporal text-attributed graphs (TTAGs). Such combination of dynamic text semantics and evolving graph struc…