Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.dss.2017.04.003 | Decision Support Systems |
Keywords | DocType | Volume |
Process management,Runtime support,Process prediction,Deep learning,Neural networks | Journal | 100 |
ISSN | Citations | PageRank |
0167-9236 | 7 | 0.52 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joerg Evermann | 1 | 447 | 35.82 |
| Jana-Rebecca Rehse | 2 | 27 | 9.25 |
| Peter Fettke | 3 | 812 | 78.37 |