References
- 1. U.S. Census Bureau [USCB]. Social Insurance and Human Services. Section 11. 2004, pp. 355-381.
- 2. Gantz, J., D. Reinsel. Extracting Value from Chaos, in IDC’s Digital Universe Study. Sponsored by EMC, 2011.
- 3. Kim, H. Y., J. Cho. Data Governance Framework for Big Data Implementation with NPS Case Analysis in Korea. – Journal of Business and Retail Management Research, Vol. 12, 2018, No 3.10.24052/JBRMR/V12IS03/ART-04
- 4. Hussain, K., E. Prieto. Big Data in the Finance and Insurance Sectors. Book of New Horizons for a Data-Driven Economy, 2016, pp. 209-223.10.1007/978-3-319-21569-3_12
- 5. Song, T., S. Ryu. Big Data Analysis Framework for Healthcare and Social Sectors in Korea. – Healthcare Informatics Research, Vol. 21, 2015, No 1, pp. 3-9.10.4258/hir.2015.21.1.3433019625705552
- 6. Tsai, C. W., C. F. Lai, H. C. Chao, A. V. Vasilakos. Big Data Analytics: A Survey. – Journal of Big Data, Vol. 2, 2015, No 21, pp. 1-32.10.1186/s40537-015-0030-3
- 7. Bhoola, K., T. Madzhadzhi, J. Narayan, S. Strydom, H. Heerden. Insurance Regulation in Africa: Impact on Insurance and Growth Strategies. Actuarial Society of South Africa’s, Cape Town International Convention Centre, 2014, pp.145-196.
- 8. Yenkar, V., M. Bartere. Review on Data Mining with Big Data. – International Journal of Computer Science and Mobile Computing, Vol. 3, 2014, Issue 4, pp. 97-102.
- 9. García, S., S. Ramírez-Gallego, J. Luengo, J. M. Benítez, F. Herrera. Big Data Preprocessing: Methods and Prospects. BMC Big Data Analytics, 2016, pp. 1-22.10.1186/s41044-016-0014-0
- 10. Tiruveedhula, S., C. M. S. Rani, V. Narayana. A Survey on Clustering Techniques for Big Data Mining. – Indian Journal of Science and Technology, Vol 9, 2016, No 3, pp. 1-12.10.17485/ijst/2016/v9i3/75971
- 11. Bücker, T. Customer Clustering in the Insurance Sector by Means of Unsupervised Machine Learning. Internship Report, 2016, pp. 1-112.
- 12. International Labour Organization [ILO]. Social Insurance: Enhancing Social Security Right for Everyone. – Policy Brief, Vol. 3, 2014.
- 13. Cai, F., N. Le-Khac, T. Kechadi. Clustering Approaches for Financial Data Analysis: A Survey. School of Computer Science & Informatics, 2016.
- 14. Chahal, H., P. Gulia. Big Data Analytics. – Research Journal of Computer and Information Technology Sciences, Vol. 4, 2016, pp. 1-4.
- 15. Wang, C., M. Chen, E. Schifano, J. Wu, J. Yan. Statistical Methods and Computing for Big Data. – Statistics and Its Interface, 2016, pp. 399-414.10.4310/SII.2016.v9.n4.a1504159527695593
- 16. American Academy of Actuaries [AAA]. Big Data and the Role of the Actuary. Big Data Task Force, 2018.
- 17. International Labor Office [ILO]. ILO Pension Model Technical Guide, 2018.
- 18. Jadhav, A., D. Pramod, K. Ramanathan. Comparison of Performance of Data Imputation Methods for Numeric Dataset. – International Journal in Applied Artificial Intelligence, 2019, pp. 913-933.10.1080/08839514.2019.1637138
- 19. García, S., J. Luengo, F. Herrera. Preprocessing in Data Mining. Springer International Publishing, Switzerland, 2015.10.1007/978-3-319-10247-4
- 20. Aggarwal, C. C. Outlier Analysis. Second Edition. Springer, Cham, 2016.10.1007/978-3-319-47578-3
- 21. Amorima, R. C., C. Hennigb. Recovering the Number of Clusters in Data Sets with Noise Features Using Feature Rescaling Factors. – Information Sciences Journal, 2016, pp. 1-34.
- 22. Bridgelall, R. Introduction to Support Vector Machines. Lecture Notes, 2017, pp. 1-18.