Contrastive graph neural network-based camouflaged fraud detector

Author:

Deng Zexuan,Xin Guodong,Liu Yang,Wang Wei,Wang Bailing

Funder

Harbin Institute of Technology

Republic of China Ministry of Science and Technology

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference49 articles.

1. Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019;Al-Hashedi;Comput. Sci. Rev.,2021

2. Gotcha! network-based fraud detection for social security fraud;Van Vlasselaer;Manage. Sci.,2017

3. Using data mining to detect health care fraud and abuse: a review of literature;Joudaki;Global J. Health Sci.,2015

4. T.N. Kipf, M. Welling, Semi-supervised classification with graph convolutional networks, in: 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24–26, 2017, Conference Track Proceedings, 2017.

5. P. Veličković, G. Cucurull, A. Casanova, A. Romero, P. Lio, Y. Bengio, Graph attention networks, arXiv preprint arXiv:1710.10903 (2017).

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