DATE
Author:
Affiliation:
1. Institute for Basic Science, Daejeon, Republic of Korea
2. National Cheng Kung University, Tainan, Taiwan Roc
3. World Customs Organization, Brussels, Belgium
4. Nigeria Customs Service, Abuja, Nigeria
Funder
Ministry of Science and Technology, Taiwan
Institute for Basic Science
World Customs Organization
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3394486.3403339
Reference32 articles.
1. Fraud detection system: A survey
2. A survey of machine-learning and nature-inspired based credit card fraud detection techniques
3. A survey of anomaly detection techniques in financial domain
4. Bioactive Molecule Prediction Using Extreme Gradient Boosting
5. Handling class imbalance in customer churn prediction
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4. GraphFC: Customs Fraud Detection with Label Scarcity;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21
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