Publications

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Alexander Michael Rombach; Johannes Lahann; Tim Niesen; Peter Fettke
Utilizing Deep Learning for Field-Level Information Extraction from German Real Estate Tax Notices
In: Journal of Emerging Technologies in Accounting (JETA), Vol. 22, Pages 1-18, American Accounting Association, 12/2024.
Johannes Lahann; Peter Pfeiffer; Peter Fettke
LSTM-based Anomaly Detection of Process Instances: Benchmark and Tweaks
In: Proceedings of the 4th International Conference on Process Mining (Workshops). International Conference on Process Mining (ICPM-2022), Process Mining Workshops, October 23-28, Bolzano, Italy, Lecture Notes in Business Information Processing, Springer, 2023.
Peter Pfeiffer; Johannes Lahann; Peter Fettke
The Label Ambiguity Problem in Process Prediction
In: Cristina Cabanillas; Niels Frederik Garmann-Johnsen; Agnes Koschmider (Hrsg.). Business Process Management Workshops. International Workshop on Artificial Intelligence for Business Process Management (AI4BPM-2022), September 11-15, Münster, Germany, Pages 37-44, ISBN 978-3-031-25383-6, Springer International Publishing, 2023.
Nijat Mehdiyev; Lea Götz; Johannes Lahann; Peter Fettke
Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium‐sized enterprises
In: Expert Systems (EXSY), Vol. 39, Pages 1-24, Wiley, 2022.
Dominic Neu; Johannes Lahann; Peter Fettke
A systematic literature review on state-of-the-art deep learning methods for process prediction
In: Artificial Intelligence Review, Vol. Online, Springer Nature, 3/2021.
Sebastian Stephan; Johannes Lahann; Peter Fettke
A Case Study on the Application of Process Mining in Combination with Journal Entry Tests for Financial Auditing
In: Data Analytics, Control, and Risk Management. Hawaii International Conference on System Sciences (HICSS-2021), January 4-8, Hawaii/Virtual, HI, USA, Pages 5718-5728, HICSS, 1/2021.
Peter Pfeiffer; Johannes Lahann; Peter Fettke
Multivariate Business Process Representation Learning Utilizing Gramian Angular Fields and Convolutional Neural Networks
In: Artem Polyvyanyy; Moe Thandar Wynn; Amy Van Looy; Manfred Reichert (Hrsg.). Business Process Management. Business Process Management (BPM-2021), September 6-10, Rome, Italy, Pages 327-344, ISBN 978-3-030-85469-0, Springer International Publishing, 2021.
Johannes Lahann; Martin Scheid; Peter Fettke
Towards Optimal Free Trade Agreement Utilization through Deep Learning Techniques
In: Tung Bui; Ralph Sprague (Hrsg.). Proceedings of the 53rd Annual Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences (HICSS-2020), January 7-10, Maui, HI, USA, ISBN 978-0-9981331-3-3, IEEE Computer Society, 2020.
Sabine Klein; Johannes Lahann; Lea Götz; Dominic Neu; Peter Pfeiffer; Adrian Rebmann; Martin Scheid; Brian Willems; Peter Fettke
Business Process Intelligence Challenge 2020: Analysis and evaluation of a travel process
In: Proceedings of the 2nd International Conference on Process Mining. International Conference on Process Mining (ICPM-2020), located at 2nd, October 4-9, University of Padua, Italy, IEEE, 2020.
Johannes Lahann; Martin Scheid; Peter Fettke
Utilizing Machine Learning Techniques to reveal VAT Compliance Violations in Accounting Data
In: 2019 IEEE 21th Conference on Business Informatics (CBI). IEEE Conference on Business Informatics (CBI-2019), Business Analytics and Business Data Engineering, July 15-17, Moscow, Russian Federation, IEEE, 2019.