2 code implementations • 29 Nov 2019 • Timo Nolle, Alexander Seeliger, Nils Thoma, Max Mühlhäuser
In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search.
3 code implementations • 8 Feb 2019 • Timo Nolle, Stefan Luettgen, Alexander Seeliger, Max Mühlhäuser
Finally, we demonstrate that a simple set of rules can be used to utilize the output of BINet for anomaly classification.
no code implementations • 3 Mar 2018 • Timo Nolle, Stefan Luettgen, Alexander Seeliger, Max Mühlhäuser
In this paper, we propose a method, using autoencoders, for detecting and analyzing anomalies occurring in the execution of a business process.