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papersTODAY 04:00 UTC

GNN4PPM: Graph Neural Networks for Multi-Target Predictive Process Monitoring

A new arXiv paper proposes GNN4PPM, which applies relational graph convolutional networks to predictive process monitoring. The method targets several predictions at once, such as the next event in a running process, the time remaining until a trace finishes, and its eventual outcome. The authors argue that existing techniques typically address only one of these targets; the posted abstract is truncated before any experimental results are described.

arXiv GNN4PPM graph neural networks multi-target predictive process monitoring predictive process monitoring relational graph convolutional networks

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arXiv cs.LGGNN4PPM: Multi-Target Predictive Process Monitoring with Relational Graph Convolutional Networks ↗TODAY 04:00 UTC