MS_HGNN: a hybrid online fraud detection model to alleviate graph-based data imbalance
Author:
Affiliation:
1. College of Information Science and Engineering, Hunan Normal University, Changsha, Hunan, People's Republic of China
2. Department of Computer Science and Information Engineering, Providence University, Taiwan
Funder
National Natural Science Foundation of China
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Human-Computer Interaction,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2191893
Reference36 articles.
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2. Benchaji I. Douzi S. & Ouahidi B. E. (2018). Using genetic algorithm to improve classification of imbalanced datasets for credit card fraud detection (pp. 220–229). Springer.
3. A systematic study of the class imbalance problem in convolutional neural networks
4. Chen J. Hou H. Gao J. Ji Y. & Bai T. (2019). RGCN: Recurrent graph convolutional networks for target-dependent sentiment analysis. Knowledge Science Engineering and Management. 2019: 667–675.
5. An Efficient Service Recommendation Algorithm for Cyber-Physical-Social Systems
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