[1]
J. W. Yin, Y. Tang, W. Lo, and L. Lo, From big data to great services, in IEEE International Congress on Big Data (Big Data Congress 2016), San Francisco, CA, USA, 2016, pp. 165–172.
[2]
Y. W. Zhang, G. M. Cui, S. G. Deng, F. F. Chen, Y. Wang, and Q. He, Efficient query of quality correlation for service composition, IEEE Transactions on Services Computing, .
[3]
Q. He, J. Han, F. F. Chen, Y. C. Wang, R. Vasa, Y. Yang, and H. Jin, QoS-aware service selection for customizable multi-tenant service-based systems: Maturity and approaches, in IEEE 8th International Conference on Cloud Computing, New York, NY, USA, 2015, pp. 237–244.
[4]
Y. W. Zhang, G. M. Cui, Y. Wang, X. Guo, and S. Zhao, An optimization algorithm for services composition based on an improved FOA, Tsinghua Science and Technology, vol. 20, no. 1, pp. 90–99, 2015.
[5]
Y. W. Zhang, G. M. Cui, S. Zhao, and J. Tang, IFOA4WSC: A quick and effective algorithm for QoS aware service composition, International Journal of Web and Grid Services, vol. 12, no. 1, pp. 81–108, 2016.
[6]
S. G. Deng, H. Y. Wu, D. N. Hu, and J. L. Zhao, Service selection for composition with QoS correlations, IEEE Transactions on Services Computing, vol. 9, no. 2, pp. 291–303, 2016.
[7]
Y. Yu, J. Chen, S. Q. Lin, and Y. Wang, A dynamic QoS aware logistics service composition algorithm based on social network, IEEE Transactions on Emerging Topics in Computing, vol. 2, no. 4, pp. 399–410, 2014.
[8]
F. Dahan, K. El Hindi, and A. Ghoneim, Enhanced artificial bee colony algorithm for QoS-aware web service selection problem, Computing, vol. 99, no. 5, pp. 507–517, 2017.
[9]
Y. Guo, S. G. Wang, K. S. Wong, and M. H. Kim, Skyline service selection approach based on QoS prediction, International Journal of Web and Grid Services, vol. 13, no. 4, pp. 425–447, 2017.
[10]
Y. S. Xu, J. W. Yin, S. G. Deng, N. N. Xiong, and J. B. Huang, Context-aware QoS prediction for web service recommendation and selection, Expert Systems with Applications, vol. 53, pp. 75–86, 2016.
[11]
K. Su, B. Xiao, B. P. Liu, H. Q. Zhang, and Z. S. Zhang, TAP: A personalized trust-aware QoS prediction approach for web service recommendation, Knowledge-Based Systems, vol.115, pp. 55–65, 2017.
[12]
S. G. Deng, D. G. Wang, Y. Li, B. Cao, J. W. Yin, Z. H. Wu, and M. C. Zhou, A recommendation system to facilitate business process modeling, IEEE Transactions on Cybernetics, vol. 47, no. 6, pp. 1380–1394, 2017.
[13]
Y. W. Zhang, Y. Y. Zhou, F. T. Wang, Z. Sun, and Q. He, Service recommendation based on quotient space granularity analysis and covering algorithm on Spark, Knowledge-Based Systems, vol. 147, pp. 25–35, 2018.
[14]
X. Chen, Z. B. Zheng, Q. Yu, and M. R. Lyu, Web service recommendation via exploiting location and QoS information, IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 7, pp. 1913–1924, 2014.
[15]
Z. B. Zheng, H. Ma, M. R. Lyu, and I. King, QoS-aware web service recommendation by collaborative filtering, IEEE Transactions on Services Computing, vol. 4, no. 2, pp. 140–152, 2011.
[16]
L. Si and R. Jin, Flexible mixture model for collaborative filtering, in Proceedings of the 20th International Conference on Machine Learning (ICML-03), Washington, DC, USA, 2003, pp. 704–711.
[17]
X. Luo, M. C. Zhou, Y. N. Xia, and Q. S. Zhu, An efficient non-negative matrix-factorization-based approach to collaborative filtering for recommender systems, IEEE Transactions on Industrial Informatics, vol. 10, no. 2, pp. 1273–1284, 2014.
[18]
L. S. Shao, J. Zhang, Y. Wei, J. F. Zhao, B. Xie, and H. Mei, Personalized QoS prediction for web services via collaborative filtering, in IEEE International Conference on Web Services (ICWS 2007), Salt Lake City, UT, USA, 2007, pp. 439–446.
[19]
G. Linden, B. Smith, and J. York, Amazon.com recommendations: Item-to-item collaborative filtering, IEEE Internet Computing, vol. 7, no. 1, pp. 76–80, 2003.
[20]
Z. B. Zheng, H. Ma, M. R. Lyu, and I. King, WSRec: A collaborative filtering based web service recommender system, in IEEE International Conference on Web Services (ICWS 2009), Los Angeles, CA, USA, 2009, pp. 437–444.
[21]
L. Yao, Q. Z. Sheng, A. H. H. Ngu, J. Yu, and A. Segev, Unified collaborative and content-based web service recommendation, IEEE Transactions on Services Computing, vol. 8, no. 3, pp. 453–466, 2015.
[22]
M. Zhang, X. D. Liu, R. C. Zhang, and H. L. Sun, A web service recommendation approach based on QoS prediction using fuzzy clustering, in 2012 IEEE Ninth International Conference on Services Computing (SCC), Honolulu, HI, USA, 2012, pp. 138–145.
[23]
Z. B. Zheng, H. Ma, M. R. Lyu, and I. King, Collaborative web service QoS prediction via neighborhood integrated matrix factorization, IEEE Transactions on Services Computing, vol. 6, no. 3, pp. 289–299, 2013.
[24]
C. Y. Yu and L. P. Huang, CluCF: A clustering CF algorithm to address data sparsity problem, Service Oriented Computing and Applications, vol. 11, no. 1, pp. 33–45, 2017.
[25]
L. Zhang and B. Zhang, A geometrical representation of McCulloch-pitts neural model and its applications, IEEE Transactions on Neural Networks, vol. 10, no. 4, pp. 925–929, 1999.
[26]
T. Wu, L. Zhang, and Y. P. Zhang, Kernel covering algorithm for machine learning, Chinese Journal of Computers, vol. 28, no. 8, pp. 1295–1301, 2005.
[27]
L. Zhang and B. Zhang, A geometrical representation of M-P neural model and its applications, Chinese Journal of Software, vol. 9, no. 5, pp. 334–338, 1998.
[28]
Y. L. Zhang, Z. B. Zheng, and M. R. Lyu, WSPred: A time-aware personalized QoS prediction framework for services, in 2011 22nd IEEE International Symposium on Software Reliability Engineering (ISSRE), Hiroshima, Japan, 2011, pp. 210–219.
[29]
Z. Zheng and M. R. Lyu, Personalized reliability prediction of web services, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 22, no. 2, pp. 1–25, 2013.
[30]
C. Wu, W. Qiu, Z. Zheng, X. Wang, and X. Yang, QoS prediction of web services based on two-phase k-means clustering, in IEEE International Conference on Web Services (ICWS 2015), New York, NY, USA, 2015, pp. 161–168.