Predicting process behaviour using deep learning

作者:

Highlights:

• A deep learning approach is applied to process prediction.

• Recurrent neural network predicts next process step.

• Experimental evaluation shows improvements to state-of-the art prediction precision.

• Proposed method can successfully predict resource and organizational information.

• Proposed method can successfully predict remainder-of-case.

摘要

Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real datasets and our results surpass the state-of-the-art in prediction precision.

论文关键词:Process management,Runtime support,Process prediction,Deep learning,Neural networks

论文评审过程:Received 8 July 2016, Revised 22 March 2017, Accepted 5 April 2017, Available online 17 April 2017, Version of Record 24 July 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2017.04.003