2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024
GACL: Graph Attention Collaborative Learning for Temporal QoS Prediction
Shengxiang Hu, Guobing Zou, Bofeng Zhang +4
Accurate prediction of temporal QoS is crucial for maintaining service reliability and enhancing user satisfaction in dynamic service-oriented environments. However, current method…
cs.AI2024★ 2 cited
Large Language Model Meets Graph Neural Network in Knowledge Distillation
Shengxiang Hu, Guobing Zou, Song Yang +3
In service-oriented architectures, accurately predicting the Quality of Service (QoS) is crucial for maintaining reliability and enhancing user satisfaction. However, significant c…
cs.LG2023★ 2 cited
Dynamic Graph Representation Learning via Edge Temporal States Modeling and Structure-reinforced Transformer
Shengxiang Hu, Guobing Zou, Song Yang +3
Dynamic graph representation learning has emerged as a crucial research area, driven by the growing need for analyzing time-evolving graph data in real-world applications. While re…