Alexander Seeliger
Alexander Seeliger
Telecooperation, Computer Science
Потвърден имейл адрес: tk.informatik.tu-darmstadt.de
Заглавие
Позовавания
Позовавания
Година
Analyzing business process anomalies using autoencoders
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Machine Learning 107 (11), 1875-1893, 2018
512018
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
382016
BINet: multivariate business process anomaly detection using deep learning
T Nolle, A Seeliger, M Mühlhäuser
International Conference on Business Process Management, 271-287, 2018
332018
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
332015
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
272017
Binet: Multi-perspective business process anomaly classification
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Information Systems, 101458, 2019
262019
ProcessExplorer: intelligent process mining guidance
A Seeliger, AS Guinea, T Nolle, M Mühlhäuser
International Conference on Business Process Management, 216-231, 2019
122019
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
92018
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
82020
Process compliance checking using taint flow analysis
A Seeliger, T Nolle, B Schmidt, M Mühlhäuser
62016
A semantic browser for linked open data
A Seeliger, H Paulheim
62012
ProcessExplorer: An Interactive Visual Recommendation System for Process Mining
A Seeliger, T Nolle, M Mühlhäuser
KDD Workshop on Interactive Data Exploration and Analytics, 2018
52018
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
32016
Case2vec: advances in representation learning for business processes
S Luettgen, A Seeliger, T Nolle, M Mühlhäuser
International Conference on Process Mining, 162-174, 2020
22020
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
A Method for Debugging Process Discovery Pipelines to Analyze the Consistency of Model Properties
C Klinkmüller, A Seeliger, R Müller, L Pufahl, I Weber
EasyChair, 2021
12021
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
12017
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
2021
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
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