Spatiotemporal Graph Neural Network-Incorporated Latent Factorization of Tensors for Dynamic QoS EstimationOA
Spatiotemporal Graph Neural Network-Incorporated Latent Factorization of Tensors for Dynamic QoS Estimation
Xin Luo;Fanghui Bi;Tiantian He
College of Computer and Information Science,Southwest University,Chongqing 400715,ChinaCollege of Computer and Information Science,Southwest University,Chongqing 400715,China||NetEase,Hangzhou 310000,ChinaCenter for Frontier AI Research,Institute of High Performance Computing,Singapore Institute of Manufacturing Technology(SIMTech),Agency for Science,Technology and Research(A*STAR),Singapore 699010,Singapore
Cloud servicedata sciencedynamic quality-of-ser-vice estimationgraph convolutional networks(GCNs)latent factor-ization of tensorslatent feature analysisnon-euclidean datarepre-sentation learningtensor product
Cloud servicedata sciencedynamic quality-of-ser-vice estimationgraph convolutional networks(GCNs)latent factor-ization of tensorslatent feature analysisnon-euclidean datarepre-sentation learningtensor product
《自动化学报（英文版）》 2026 (7)
1642-1656,15
This work was supported by the National Key Research and Development Program of China(2024YFF0908200),the National Natural Science Foundation of China(62272078),and Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069).
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