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Alexander Seeliger
Alexander Seeliger
Telecooperation, Computer Science
Bestätigte E-Mail-Adresse bei tk.informatik.tu-darmstadt.de
Titel
Zitiert von
Zitiert von
Jahr
Analyzing business process anomalies using autoencoders
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Machine Learning 107, 1875-1893, 2018
992018
Binet: Multi-perspective business process anomaly classification
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Information Systems 103, 101458, 2022
712022
BINet: multivariate business process anomaly detection using deep learning
T Nolle, A Seeliger, M Mühlhäuser
International Conference on Business Process Management, 271-287, 2018
692018
Unsupervised anomaly detection in noisy business process event logs using denoising autoencoders
T Nolle, A Seeliger, M Mühlhäuser
Discovery Science: 19th International Conference, DS 2016, Bari, Italy …, 2016
602016
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
512017
Upgrading wireless home routers for enabling large-scale deployment of cloudlets
C Meurisch, A Seeliger, B Schmidt, I Schweizer, F Kaup, M Mühlhäuser
Mobile Computing, Applications, and Services: 7th International Conference …, 2015
462015
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
262020
ProcessExplorer: intelligent process mining guidance
A Seeliger, A Sánchez Guinea, T Nolle, M Mühlhäuser
Business Process Management: 17th International Conference, BPM 2019, Vienna …, 2019
242019
Finding structure in the unstructured: hybrid feature set clustering for process discovery
A Seeliger, T Nolle, M Mühlhäuser
Business Process Management: 16th International Conference, BPM 2018, Sydney …, 2018
162018
Learning of process representations using recurrent neural networks
A Seeliger, S Luettgen, T Nolle, M Mühlhäuser
International Conference on Advanced Information Systems Engineering, 109-124, 2021
122021
Case2vec: Advances in representation learning for business processes
S Luettgen, A Seeliger, T Nolle, M Mühlhäuser
International Conference on Process Mining, 162-174, 2020
122020
Process compliance checking using taint flow analysis
A Seeliger, T Nolle, B Schmidt, M Mühlhäuser
102016
Process explorer: an interactive visual recommendation system for process mining
A Seeliger, T Nolle, M Mühlhäuser
KDD Workshop on Interactive Data Exploration and Analytics, 2018
72018
A semantic browser for linked open data
A Seeliger, H Paulheim
62012
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
52016
Inferring a Multi-perspective Likelihood Graph from Black-Box Next Event Predictors
Y Gerlach, A Seeliger, T Nolle, M Mühlhäuser
International Conference on Advanced Information Systems Engineering, 19-35, 2022
32022
Can we find better process models? process model improvement using motif-based graph adaptation
A Seeliger, M Stein, M Mühlhäuser
Business Process Management Workshops: BPM 2017 International Workshops …, 2018
32018
A method for debugging process discovery pipelines to analyze the consistency of model properties
C Klinkmüller, A Seeliger, R Müller, L Pufahl, I Weber
International Conference on Business Process Management, 65-84, 2021
22021
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
22019
Discovering Process-Based Drivers for Case-Level Outcome Explanation
P Li, H Zhang, X Chu, A Seeliger, C Yu
International Conference on Process Mining, 165-178, 2023
2023
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