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Supplementary material for the article "Predictive Business Process Monitoring with LSTM Neural Networks" by Niek Tax, Ilya Verenich, Marcello La Rosa and Marlon Dumas.

The code provided in this repository can be readily used to perform the following predictive tasks:

• Prediction of the next type of activity to be executed in a running process instance
• Prediction of the timestamp of the next type of activity to be executed
• Prediction of the continuation of a running instance, i.e. its suffix
• Prediction of the remaining cycle time of an instance

For more details, please refer to the project page

If you the code from this repository, please cite our paper:

@inproceedings{Tax2017,
  title={Predictive business process monitoring with {LSTM} neural networks},
  author={Tax, Niek and Verenich, Ilya and La Rosa, Marcello and Dumas, Marlon},
  booktitle={Proceedings of the 29th International Conference on Advanced Information Systems Engineering},
  year={2017},
  pages={477--492},
  publisher={Springer}
}