General

Mingsheng Shang

PhD, Professor

Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences


Email: msshang@cigit.ac.cn
Tel: 023-65936003
Address:  No.266 Fangzheng Avenue,Shuitu Hi-tech Industrial Park, Shuitu Town, Beibei District, Chongqing 

Postcode: 400714 

Research Areas

Big Data Analysis and Applicayions
Intelligent Information Processing
Recommender Systems


Education

2003-09--2007-12  University of Electronic Science and Technology   Ph.D.
2000-09--2003-05   University of Electronic Science and Technology   M.S.


Experience

2015-07~Present    Professor & PhD Supervisor, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences

2014-08~2015-01   Visiting Scholar, University of Fribourg

2011-08~2011-10   Visiting Scholar, University of Rochester

2010-08~2015-07   Professor & PhD Supervisor, University of Electronic Science and Technology

2007-12~2009-01   Visiting Scholar, University of Minnesota

2002-02~2010-07   Lecturer/Associate Professor, University of Electronic Science and Technology

1995-07~2002-01   Assistant Professor / Lecturer , Sichuan Normal University

Publications

网络舆情信息分析与处理技术, WLYX, 科学出版社, 2015-02, First Author

Papers

​1.D. Wu, X. Luo, M. Shang, Y. He, G. Wang and X. Wu, "A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction," in IEEE Transactions on Knowledge and Data Engineering.    doi: 10.1109/TKDE.2020.3014302

2.M. Shang, Y. Yuan, X. Luo and M. Zhou, "An α -β -Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences," in IEEE Transactions on Cybernetics.  doi: 10.1109/TCYB.2020.3026425

3.X. Luo, M. Zhou, S. Li, L. Hu and M. Shang, "Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications," in IEEE Transactions on Cybernetics, vol. 50, no. 5, pp. 1844-1855, May 2020. doi:10.1109/TCYB.2019.2894283

4.D. WU, Q. He, X. Luo, M. Shang, Y. He and G. Wang, "A Posterior-neighborhood-regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction," in IEEE Transactions on Services Computing.  doi: 10.1109/TSC.2019.2961895

5.D. Wu, M. Shang, X. Luo and Z. Wang, "An L₁-and-L₂-Norm-Oriented Latent Factor Model for Recommender Systems," in IEEE Transactions on Neural Networks and Learning Systems.        doi: 10.1109/TNNLS.2021.3071392

6.L. Xin, Y. Yuan, M. Zhou, Z. Liu and M. Shang, "Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 8, pp. 4612-4623, Aug. 2021.    doi: 10.1109/TSMC. 2019. 2931468

7.D. Wu, X. Luo, M. Shang, Y. He, G. Wang and M. Zhou, "A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 7, pp. 4285-4296, July 2021.    doi: 10.1109 /TSMC.2019.2931393

8.X. Luo, Z. Wang and M. Shang, "An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 6, pp. 3522-3532, June 2021. doi: 10.1109/TSMC.2019.2930525

9.X. Luo, Z. Liu, S. Li, M. Shang and Z. Wang, "A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 1, pp. 610-620, Jan. 2021.    doi: 10.1109/TSMC.2018.2875452

10.X. Luo, M. Zhou, S. Li and M. Shang, "An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications," in IEEE Transactions on Industrial Informatics, vol. 14, no. 5, pp. 2011-2022, May 2018.    doi: 10.1109/TII.2017.2766528

11.D. Wu, X. Luo, G. Wang, M. Shang, Y. Yuan and H. Yan, "A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications," in IEEE Transactions on Industrial Informatics, vol. 14, no. 3, pp. 909-920, March 2018.    doi: 10.1109/TII.2017.2737827

12.X. Luo, J. Sun, Z. Wang, S. Li and M. Shang, "Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications," in IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3098-3107, Dec. 2017.                   doi: 10.1109/TII.2017.2724769

13.X. Luo, M. Zhou, S. Li, D. Wu, Z. Liu and M. Shang, "Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems," in IEEE Transactions on Big Data, vol. 7, no. 1, pp. 227-240, 1 March 2021.   doi: 10.1109/TBDATA.2019.2916868

14.Y. Zhong, L. Jin, M. Shang and X. Luo, "Momentum-incorporated Symmetric Non-negative Latent Factor Models," in IEEE Transactions on Big Data.    doi: 10.1109/TBDATA. 2020. 3012656

15.Y. Yuan, Q. He, X. Luo and M. Shang, "A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices," in IEEE Transactions on Big Data. doi: 10.1109/TBDATA.2020.2988778

16.X. Shi, Q. He, X. Luo, Y. Bai and M. Shang, "Large-scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems," in IEEE Transactions on Big Data.  doi: 10.1109/TBDATA.2020.2973141

17.Q. Wang, B. Peng, X. Shi, T. Shang and M. Shang, "DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction," in IEEE Access, vol. 7, pp. 60186-60198, 2019.     doi: 10.1109/ACCESS.2019.2915531

18.M. Shang, X. Luo, Z. Liu, J. Chen, Y. Yuan and M. Zhou, "Randomized latent factor model for high-dimensional and sparse matrices from industrial applications," in IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 1, pp. 131-141, January 2019.    doi: 10.1109/JAS.2018.7511189

19.X. Luo, M. Zhou, M. Shang, S. Li and Y. Xia, "A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices," in IEEE Access, vol. 4, pp. 2649-2655, 2016. doi: 10.1109/ACCESS.2016.2556680

20.X. Luo, Z. Liu, M. Shang, J. Lou and M. Zhou, "Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization," in IEEE Transactions on Network Science and Engineering, vol. 8, no. 1, pp. 463-476, 1 Jan.-March 2021.   doi: 10.1109/TNSE.2020.3040407

21.Q. Li, M. Shang, "BALFA: A Brain Storm Optimization-based Adaptive Latent Factor Analysis Model, " in Information Sciences, August 2021.     doi.org/10.1016/j.ins.2021.08.057.

22.B Peng, L Jin, M Shang, "Multi-robot competitive tracking based on k-WTA neural network with one single neuron, " in Neurocomputing, vol. 460, pp. 1-8, 14 October 2021.  doi.org/10.1016/j.neucom.2021.07.020

23.Q Wang, M Chen, M Shang, X Luo, "A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction, " in Neurocomputing, vol. 367, pp. 299-307, 20 November 2019.    doi.org/10.1016/j.neucom.2019.08.026

24.Y Yuan, X Luo, MS Shang, " Effects of preprocessing and training biases in latent factor models for recommender systems, " in Neurocomputing, vol. 275, pp. 2019-2030, 31 January 2018. doi.org/10.1016/j.neucom.2017.10.040

25.D Wu, M Shang, X Luo, J Xu, H Yan, W Deng, G Wang, " Self-training semi-supervised classification based on density peaks of data, " in Neurocomputing, vol. 275, pp.  180-191, 31 January 2018. doi.org/10.1016/j.neucom.2017.05.072

26.QX Wang, X Luo, Y Li, XY Shi, L Gu, MS Shang, " Incremental Slope-one recommenders," in Neurocomputing, vol. 272, pp.  606-618, 10 January 2018. doi.org/10.1016/j.neucom.2017.07.033

27.X Shi, X Luo, M Shang, L Gu, " Long-term performance of collaborative filtering based recommenders in temporally evolving systems, " in Neurocomputing, vol. 267, pp.  635-643, 6 December 2017.doi.org/10.1016/j.neucom.2017.06.026

28.M Liu, B Peng, M Shang, " Lower limb movement intention recognition for rehabilitation robot aided with projected recurrent neural network, "in Complex & Intelligent Systems, pp. 1-12, 2021.             

29.B Zhou, M Shang, L Feng, K Shan, L Feng, J Ma, X Liu, L Wu, " Long-term remote tracking the dynamics of surface water turbidity using a density peaks-based classification: A case study in the Three Gorges Reservoir, China, " in Ecological Indicators, vol. 116, pp. 106539, September 2020.    doi.org/10.1016/j.ecolind.2020.106539

30.K Shan, X Wang, H Yang, B Zhou, L Song, M Shang, " Use statistical machine learning to detect nutrient thresholds in Microcystis blooms and microcystin management, " in Harmful algae , vol. 94, pp. 101807, April 2020.  doi.org/10.1016/j.hal.2020.101807

31.K Shan, M Shang, B Zhou, L Li, X Wang, H Yang, L Song, " Application of Bayesian network including Microcystis morphospecies for microcystin risk assessment in three cyanobacterial bloom-plagued lakes, China, " in Harmful Algae, vol. 83, pp. 14-24, March 2019. doi.org/10.1016/j.hal.2019.01.005

32.B Zhou, M Shang, S Zhang, L Feng, X Liu, L Wu, L Feng, K Shan, " Remote examination of the seasonal succession of phytoplankton assemblages from time-varying trends, " in Journal of environmental management, vol. 246, pp.  687-694, 15 September 2019. doi.org/10.1016/j.jenvman.2019.06.035

33.W Tian, M He, W Guo, W Huang, X Shi, M Shang,  AN Toosi, R Buyya, " On minimizing total energy consumption in the scheduling of virtual machine reservations, "  in Journal of Network and Computer Applications, vol.  113, pp.  64-74, 1 July 2018. doi.org/10.1016/j.jnca.2018.03.033

34.B Zhou, M Shang, G Wang, S Zhang, L Feng, X Liu, L Wu, K Shan, "Distinguishing two phenotypes of blooms using the normalised difference peak-valley index (NDPI) and Cyano-Chlorophyta index (CCI), " in Science of the Total Environment, vol. 628, pp.  848-857, 1 July 2018. doi.org/10.1016/j.scitotenv.2018.02.097            

35.D Wu, H Yan, M Shang, K Shan, G Wang, "Water eutrophication evaluation based on semi-supervised classification: A case study in Three Gorges Reservoir, " in Ecological indicators, vol. 81, pp. 362-372, October 2017.  doi.org/10.1016/j.ecolind.2017.06.004

36.H Yan, D Wu, Y Huang, G Wang, M Shang, J Xu, X Shi, K Shan, B Zhou, "Water eutrophication assessment based on rough set and multidimensional cloud model, " in   Chemometrics and Intelligent Laboratory Systems, vol. 164, pp. 103-112, 2017.

37.J Chen, X Luo, Y Yuan, M Shang, Z Ming, Z Xiong, "Performance of latent factor models with extended linear biases, " in Knowledge-Based Systems, vol. 123, pp. 128-136, 1 May 2017. doi.org/10.1016/j.knosys.2017.02.010

38.H Yan, Y Huang, G Wang, X Zhang, M Shang, L Feng, J Dong, K Shan, "Water eutrophication evaluation based on rough set and petri nets: A case study in Xiangxi-River, Three Gorges Reservoir, " in Ecological Indicators, vol.  69, pp. 463-472, October 2016. doi.org/10.1016/j.ecolind.2016.05.010

39.HY Yan, XR Zhang, JH Dong, MS Shang, K Shan, D Wu, Y Yuan, X Wang, "Spatial and temporal relation rule acquisition of eutrophication in Da’ning River based on rough set theory, " in Ecological indicators, vol. 66, pp. 180-189, July 2016.               doi.org/10.1016/j.ecolind.2016.01.032.


Patents
( 1 ) A prediction method and system for the popular goods in the electronic commerce system, 2014, First Author, No. 201410524541.4
( 2 ) A method of an online social media system for detecting users preferring malicious score  2014, First Author, No. 201410638173.6
( 3 ) A personalized recommendation method and system based on the key users, 2015, Second Author, No. 201510157504.9 
( 4 ) A recommendation method  in the electronic commerce system, 2015, First Author, No. 201510925459.7
( 5 ) prediction method for quantity of forwarding in weibo, 2015, First Author, No. 201510909377.3
( 6 )  A recommendation method for customizaiton  in online systems, 2015, First AuthorNo.201510827825.5

Students

已指导学生

彭彬彬  硕士研究生  081203-计算机应用技术  

现指导学生

袁野  博士研究生  081203-计算机应用技术  

徐晓宇  博士研究生  081203-计算机应用技术  

王韬  硕士研究生  081203-计算机应用技术  

冉龙宇  硕士研究生  085211-计算机技术