DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks

Timo Nolle, Alexander Seeliger, Nils Thoma +1

In this paper, we propose DeepAlign, a novel approach to multi-perspective process anomaly correction, based on recurrent neural networks and bidirectional beam search. At the core…