Detecting Anomalous Events in Object-centric Business Processes via Graph Neural Networks
By Alessandro Niro, Michael Werner
Rating
1340
Battle Count: 33
Relevance
6/10
While not directly applicable to trading, the anomaly detection approach could be adapted for financial process monitoring and fraud detection
Implementation Complexity
7/10
Requires understanding of graph neural networks and object-centric process mining concepts
Reproducibility
4/5
Code and datasets are publicly available, experimental setup is well-described
About this paper
Methodology: Graph Convolutional Autoencoder. Problem types: Anomaly Detection, Graph Learning.
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