AI RESEARCH
Anomaly Resilient Temporal QoS Prediction using Hypergraph Convoluted Transformer Network
arXiv CS.LG
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ArXi:2410.17762v3 Announce Type: replace Quality-of-Service (QoS) prediction is a critical task in the service lifecycle, enabling precise and adaptive service recommendations by anticipating performance variations over time in response to evolving network uncertainties and user preferences. However, contemporary QoS prediction methods frequently encounter data sparsity and cold-start issues, which hinder accurate QoS predictions and limit the ability to capture diverse user preferences.