|
[1]
|
Mashey, J.R. (1997) Big Data and the Next Wave of Infra-Stress. Computer Science Division Seminar, University of California, Berkeley.
|
|
[2]
|
Laney, D. (2001) 3-D Data Management: Controlling Data Volume, Velocity and Variety. Application Delivery Strate-gies by META Group Inc., Stamford, 949.
|
|
[3]
|
Majumder, N., Poria, S., Gelbukh, A. and Cambria, E. (2017) Deep Learning-Based Document Modeling for Personality Detection from Text. IEEE Intelligent Systems, 32, 74-79. [Google Scholar] [CrossRef]
|
|
[4]
|
Zhang, Q., Yang, L.T. and Chen, Z. (2016) Deep Computation Model for Unsuper-vised Feature Learning on Big Data. IEEE Transactions on Services Computing, 9, 161-171. [Google Scholar] [CrossRef]
|
|
[5]
|
Grushka-Cockayne, Y., Jose, V.R.R. and Lichtendahl, K.C. (2017) Ensembles of Overfit and Overconfident Forecasts. Management Science, 63, 1110-1130. [Google Scholar] [CrossRef]
|
|
[6]
|
Amin, J., Sharif, M., Yasmin, M. and Fernandes, S.L. (2018) Big Data Analysis for Brain Tumor Detection: Deep Convolutional Neural Networks. Future Generation Computer Systems, 87, 290-297. [Google Scholar] [CrossRef]
|
|
[7]
|
Zhou, L.N., Pan, S.M., Wang, J.W. and Vasilakos, A.V. (2017) Machine Learning on Big Data: Opportunities and Challenges. Neurocomputing, 237, 350-361. [Google Scholar] [CrossRef]
|
|
[8]
|
Huck, N. (2019) Large Data Sets and Machine Learning: Applications to Sta-tistical Arbitrage. European Journal of Operational Research, 278, 330-342. [Google Scholar] [CrossRef]
|
|
[9]
|
Jeon, S. and Hong, B. (2016) Monte Carlo Simulation-Based Traffic Speed Forecasting Using Historical Big Data. Future Generation Com-puter Systems, 65, 182-195. [Google Scholar] [CrossRef]
|
|
[10]
|
赵鹏军, 李铠. 大数据方法对于缓解城市交通拥堵的作用的理论分析[J]. 现代城市研究, 2014(10): 25-30.
|
|
[11]
|
惠榛, 李昊, 张敏, 等. 面向医疗大数据的风险自适应的访问控制模型[J]. 通信学报, 2015, 36(12): 190-199.
|