A Hybrid Model for QoS Prediction based on Improved Conditional Variational Autoencoder

As a nonfunctional attribute of Web services, Quality of Service (QoS) is a crucial criterion that researchers utilize to develop personalized service recommendation. The QoS history is thin and contains noisy data because of the network environment and other inevitable factors. In order to increase...

Celý popis

Podrobná bibliografia

Vydané v:	2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) s. 339 - 346
Hlavní autori:	Wu, Mengwei, Lu, Qin, Wang, Yingxue, Wang, Yichao, Chen, Huanyu, Li, Weixiao
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2022
Predmet:	BiasSVD Conditional Variational Autoencoder Correlation coefficient Independent Sample T-test Matrix decomposition Noise measurement Predictive models QoS prediction Quality of service Service recommendation Sparse matrices Web services
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!