An Analysis of Novel Money Laundering Data Using Heterogeneous Graph Isomorphism Networks. FinCEN Files Case Study
Aim: This study aimed to develop and apply the novel HexGIN (Heterogeneous extension for Graph Isomorphism Network) model to the FinCEN Files case data and compare its performance with existing solutions, such as the SAGE-based graph neural network and Multi-Layer Perceptron (MLP), to demonstrate it...
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| Format: | Article |
| Language: | English |
| Published: |
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
2024-07-01
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| Series: | Ekonometria |
| Subjects: | |
| Online Access: | https://journals.ue.wroc.pl/eada/article/view/1181 |
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