OffDQ: An Offline Deep Learning Framework for QoS Prediction-Reference-Cited by-同舟云学术

OffDQ: An Offline Deep Learning Framework for QoS Prediction

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2022
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Author:

Chattopadhyay Soumi¹,Chanda Richik¹,Kumar Suraj¹,Adak Chandranath²

Affiliation:

1. Indian Institute of Information Technology Guwahati, India

2. Indian Institute of Information Technology, Lucknow, India

Funder

Science and Engineering Research Board, Department of Science and Technology, Government of India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3485447.3512107

Reference34 articles.

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3. S. Chattopadhyay A. Banerjee and T. Mukherjee. 2016. A Framework for Top Service Subscription Recommendations for Service Assemblers. In IEEE SCC. 332–339. S. Chattopadhyay A. Banerjee and T. Mukherjee. 2016. A Framework for Top Service Subscription Recommendations for Service Assemblers. In IEEE SCC. 332–339.

4. An accurate and efficient web service QoS prediction model with wide-range awareness

5. . CASR-TSE: Context-Aware Web Services Recommendation for Modeling Weighted Temporal-Spatial Effectiveness;Fan X.;IEEE TSC,2021

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