| Upgrading wireless home routers for enabling large-scale deployment of cloudlets C Meurisch, A Seeliger, B Schmidt, I Schweizer, F Kaup, M Mühlhäuser International Conference on Mobile Computing, Applications, and Services, 12-29, 2015 | 31 | 2015 |
| Unsupervised anomaly detection in noisy business process event logs using denoising autoencoders T Nolle, A Seeliger, M Mühlhäuser International conference on discovery science, 442-456, 2016 | 24 | 2016 |
| BINet: multivariate business process anomaly detection using deep learning T Nolle, A Seeliger, M Mühlhäuser International Conference on Business Process Management, 271-287, 2018 | 23 | 2018 |
| Analyzing business process anomalies using autoencoders T Nolle, S Luettgen, A Seeliger, M Mühlhäuser Machine Learning 107 (11), 1875-1893, 2018 | 21 | 2018 |
| Detecting concept drift in processes using graph metrics on process graphs A Seeliger, T Nolle, M Mühlhäuser Proceedings of the 9th Conference on Subject-Oriented Business Process …, 2017 | 16 | 2017 |
| Finding structure in the unstructured: hybrid feature set clustering for process discovery A Seeliger, T Nolle, M Mühlhäuser International Conference on Business Process Management, 288-304, 2018 | 8 | 2018 |
| Binet: Multi-perspective business process anomaly classification T Nolle, S Luettgen, A Seeliger, M Mühlhäuser Information Systems, 101458, 2019 | 7 | 2019 |
| ProcessExplorer: intelligent process mining guidance A Seeliger, AS Guinea, T Nolle, M Mühlhäuser International Conference on Business Process Management, 216-231, 2019 | 7 | 2019 |
| Process compliance checking using taint flow analysis A Seeliger, T Nolle, B Schmidt, M Mühlhäuser | 6 | 2016 |
| A semantic browser for linked open data A Seeliger, H Paulheim | 6 | 2012 |
| DeepAlign: Alignment-Based Process Anomaly Correction Using Recurrent Neural Networks T Nolle, A Seeliger, N Thoma, M Mühlhäuser International Conference on Advanced Information Systems Engineering, 319-333, 2020 | 3 | 2020 |
| What Belongs Together Comes Together: Activity-centric Document Clustering for Information Work A Seeliger, B Schmidt, I Schweizer, M Mühlhäuser Proceedings of the 21st International Conference on Intelligent User …, 2016 | 3 | 2016 |
| ProcessExplorer: Interactive Visual Exploration of Event Logs with Analysis Guidance A Seeliger, M Ratzke, T Nolle, M Mühlhäuser International Conference on Process Mining - ICPM Demo Track 2019, 24-27, 2019 | 1* | 2019 |
| ProcessExplorer: An Interactive Visual Recommendation System for Process Mining A Seeliger, T Nolle, M Mühlhäuser | 1 | 2018 |
| Can We Find Better Process Models? Process Model Improvement Using Motif-Based Graph Adaptation A Seeliger, M Stein, M Mühlhäuser International Conference on Business Process Management, 230-242, 2017 | 1 | 2017 |
| Extended synthetic event logs for multi-perspective trace clustering A Seeliger, S Lüttgen, M Mühlhäuser, T Nolle | | 2020 |
| Intelligent Computer-assisted Process Mining A Seeliger Technische Universität Darmstadt, 2020 | | 2020 |
| UPA'19: 4th international workshop on ubiquitous personal assistance AS Guinea, A Seeliger, V Pejović, U Naeem, PM Scholl, C Mihale-Wilson, ... Adjunct Proceedings of the 2019 ACM International Joint Conference on …, 2019 | | 2019 |
| Synthetic event logs for multi-perspective trace clustering A Seeliger, T Nolle, M Mühlhäuser | | 2018 |
| Beyond Process Mining-Process Mining für Prozesstransformation und ERP-Einführungen C Fleig, A Seeliger, A Knissling IM+ io, 90, 2017 | | 2017 |
Max MühlhäuserProfessor of Computer Science, Technische Universität DarmstadtVerified email at informatik.tu-darmstadt.de
