PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances

arXiv:2404.06267v1 Announce Type: new
Abstract: We present PGTNet, an approach that transforms event logs into graph datasets and leverages graph-oriented data for training Process Graph Transformer Networks to predict the remaining time of business process instances. PGTNet consistently outperforms state-of-the-art deep learning approaches across a diverse range of 20 publicly available real-world event logs. Notably, our approach is most promising for highly complex processes, where existing deep learning approaches encounter difficulties stemming from their limited ability to learn control-flow relationships …

abstract art arxiv business business process cs.ai cs.lg data datasets deep learning diverse event graph instances logs network networks prediction process state training transformer transformer network type