Fraud Detection Call Detail Record Using Machine Learning in Telecommunications Company
Author:
Publisher
ASTES Journal
Subject
Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)
Link
https://www.astesj.com/publications/ASTESJ_050409.pdf
Reference20 articles.
1. M. Arafat, A. Qusef and G. Sammour, "Detection of Wangiri Telecommunication fraud using ensemble learning" in 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), 2019. https://doi.org/10.1109/JEEIT.2019.8717528
2. M. Liu, J. Liao, J. Wang and Q. Qi, "AGRM: Attention-based graph representation model for Telecom fraud detection" in ICC 2019-2019 IEEE International Conference on Communications (ICC), 2019. https://doi.org/10.1109/ICC.2019.8761665
3. S. Gee, Fraud and Fraud Detection: A Data Analytics Approach, Hoboken: John Wiley & Sons, Inc., 2015.
4. V. Jain, "Perspective analysis of telecommunication fraud detection using data stream analytics and neural network classification based data mining" International Journal of Information Technology, 9(3), 303-310, 2017. https://doi.org/10.1007/s41870-017-0036-5
5. T. Russell, Signaling system# 7 (Vol. 2), New York: McGraw-Hill, 2002.
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