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Alexander Seeliger
Alexander Seeliger
Telecooperation, Computer Science
Verified email at tk.informatik.tu-darmstadt.de
Title
Cited by
Cited by
Year
Analyzing business process anomalies using autoencoders
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Machine Learning 107, 1875-1893, 2018
732018
BINet: multivariate business process anomaly detection using deep learning
T Nolle, A Seeliger, M Mühlhäuser
Business Process Management: 16th International Conference, BPM 2018, Sydney …, 2018
522018
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
512016
Binet: Multi-perspective business process anomaly classification
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Information Systems 103, 101458, 2022
472022
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
402015
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
382017
DeepAlign: alignment-based process anomaly correction using recurrent neural networks
T Nolle, A Seeliger, N Thoma, M Mühlhäuser
Advanced Information Systems Engineering: 32nd International Conference …, 2020
182020
ProcessExplorer: intelligent process mining guidance
A Seeliger, A Sánchez Guinea, T Nolle, M Mühlhäuser
Business Process Management: 17th International Conference, BPM 2019, Vienna …, 2019
182019
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
122018
Process compliance checking using taint flow analysis
A Seeliger, T Nolle, B Schmidt, M Mühlhäuser
82016
Learning of process representations using recurrent neural networks
A Seeliger, S Luettgen, T Nolle, M Mühlhäuser
Advanced Information Systems Engineering: 33rd International Conference …, 2021
72021
Case2vec: Advances in representation learning for business processes
S Luettgen, A Seeliger, T Nolle, M Mühlhäuser
Process Mining Workshops: ICPM 2020 International Workshops, Padua, Italy …, 2021
62021
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
62018
A semantic browser for linked open data
A Seeliger, H Paulheim
62012
A method for debugging process discovery pipelines to analyze the consistency of model properties
C Klinkmüller, A Seeliger, R Müller, L Pufahl, I Weber
Business Process Management: 19th International Conference, BPM 2021, Rome …, 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
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
22018
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
22016
Inferring a Multi-perspective Likelihood Graph from Black-Box Next Event Predictors
Y Gerlach, A Seeliger, T Nolle, M Mühlhäuser
Advanced Information Systems Engineering: 34th International Conference …, 2022
2022
Extended synthetic event logs for multi-perspective trace clustering
A Seeliger, S Lüttgen, M Mühlhäuser, T Nolle
2020
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