Titlebook: QoS Management of Web Services; Zibin Zheng,Michael R. Lyu Book 2013 Zhejiang University Press, Hangzhou and Springer-Verlag Berlin Heidel

只看該作者 · 發(fā)表于 2025-3-21 19:05:57

書目名稱QoS Management of Web Services影響因子(影響力)

書目名稱QoS Management of Web Services影響因子(影響力)學(xué)科排名

書目名稱QoS Management of Web Services網(wǎng)絡(luò)公開度

書目名稱QoS Management of Web Services網(wǎng)絡(luò)公開度學(xué)科排名

書目名稱QoS Management of Web Services被引頻次

書目名稱QoS Management of Web Services被引頻次學(xué)科排名

書目名稱QoS Management of Web Services年度引用

書目名稱QoS Management of Web Services年度引用學(xué)科排名

書目名稱QoS Management of Web Services讀者反饋

書目名稱QoS Management of Web Services讀者反饋學(xué)科排名

只看該作者 · 發(fā)表于 2025-3-21 22:47:42

QoS Evaluation of Web Services,their observed Web service QoS information. The information is stored in a centralized server and will be reused for other users. Several large-scale distributed evaluations are conducted on real-world Web services, and detailed evaluation results are publicly released for future research.

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只看該作者 · 發(fā)表于 2025-3-22 05:26:58

只看該作者 · 發(fā)表于 2025-3-22 11:30:03

Book 2013 also presents an excellent overview of QoS management of Web sciences, making it a valuable resource for researchers and graduate students in service computing. .Zibin Zheng. is an associate research fellow at the Shenzhen Research Institute, The Chinese University of Hong Kong, China. Professor .Michael R. Lyu. also works at the same institute..

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只看該作者 · 發(fā)表于 2025-3-22 23:28:07

QoS Evaluation of Web Services,ework employs the concept of user collaboration, which is the key concept of Web 2.0. In our framework, users in different geographic locations share their observed Web service QoS information. The information is stored in a centralized server and will be reused for other users. Several large-scale

只看該作者 · 發(fā)表于 2025-3-23 02:04:57

只看該作者 · 發(fā)表于 2025-3-23 05:54:53

Model-Based QoS Prediction of Web Services,ind similar users/items when the user-item matrix is very sparse. To address these drawbacks, this chapter proposes a neighborhood-integrated matrix factorization (NIMF) approach for Web service QoS value prediction. Our approach explores the social wisdom of service users by systematically fusing t

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