A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 9
Issue 3
IEEE/CAA Journal of Automatica Sinica
| Citation: | W. J. Huang, P. Y. Zhang, Y. T. Chen, M. C. Zhou, Y. Al-Turki, and A. Abusorrah, “QoS prediction model of cloud services based on deep learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 564–566, Mar. 2022. doi: 10.1109/JAS.2021.1004392
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Y. Zhang, Z. Zheng, and M. R. Lyu, “Exploring latent features for memory-based QoS prediction in cloud computing,” in Proc. of 2011 IEEE 30th In. Symp. on Reliable Distributed Systems, pp. 1–10, Nov. 2011.
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J. Zhu, P. He, Z. Zheng, and M. R. Lyu, “Online QoS prediction for runtime service adaptation via adaptive matrix factorization,” IEEE Trans. on Parallel and Distributed Systems, vol. 28, no. 10, pp. 2911–2924, Oct. 2017.
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X. Zhu, X. Jing, D. Wu, Z. He, J. Cao, D. Yue, and L. Wang, “Similarity-maintaining privacy preservation and location-aware low-rank matrix factorization for QoS prediction based web service recommendation,” IEEE Trans. on Services Computing, vol. 14, no. 3, pp. 889–902, May–Jun. 2021.
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Y. Zhang, P. Zhang, Y. Luo, and L. Ji, “Towards efficient, credible and privacy-preserving service QoS prediction in unreliable mobile edge environments,” in Proc. of 2020 In. Symp. on Reliable Distributed Systems (SRDS), pp. 309–318, Nov. 2020.
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R. Xiong, J. Wang, Z. Li, B. Li, and P. Hung, “Personalized LSTM based matrix factorization for online QoS prediction,” in Proc. of 2018 IEEE In. Conf. on Web Services (ICWS), pp. 34–41, Sept. 2018.
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X. Chen, B. Li, J. Wang, Y. Zhao, and Y. Xiong, ” Integrating EMD with multivariate LSTM for time series QoS prediction,” in Proc. of 2020 IEEE In. Conf. on Web Services (ICWS), pp. 58–65, Dec. 2020.
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Z. Zheng, Y. Zhang, and M. Lyu, “Investigating QoS of real-world web services,” IEEE Trans. on Services Computing, vol. 7, no. 1, pp. 32–39, Jan.–Mar. 2014.
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R. Salakhutdinov and A. Mnih, “Probabilistic matrix factorization,” Advances Neural Information Processing Systems, vol. 20, no. 1, pp. 1257–1264, Dec. 2007.
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G. Zou, et al., “NDMF: Neighborhood-integrated deep matrix factorization for service QoS prediction,” IEEE Trans. on Network and Service Management, vol. 17, no. 4, pp. 2717–2730, Dec. 2020.
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Y. Zhang, K. Wang, Q. He, F. Chen, S. Deng, Z. Zheng, and Y. Yang, “Covering-based web service quality prediction via neighborhood-aware matrix factorization, ” IEEE Trans. on Services Computing, pp. 1–12, Jan. 2019.
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W. Yue, Z. Wang, J. Zhang, and X. Liu, “An overview of recommendation techniques and their applications in healthcare,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 701–717, Apr. 2021.
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| [12] |
S. Imran, T. Mahmood, A. Morshed, and T. Sellis, “Big data analytics in healthcare − A systematic literature review and roadmap for practical implementation,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 1–22, Jan. 2021.
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