| Abstracting process mining event logs from process-state data to monitor control-flow of industrial manufacturing processes M Mayr, S Luftensteiner, GC Chasparis Procedia Computer Science 200, 1442-1450, 2022 | 13 | 2022 |
| Filter-based feature selection methods for industrial sensor data: a review S Luftensteiner, M Mayr, G Chasparis International Conference on Big Data Analytics and Knowledge Discovery, 242-249, 2021 | 6 | 2021 |
| Generalized input-output hidden-markov-models for supervising industrial processes GC Chasparis, S Luftensteiner, M Mayr Procedia Computer Science 200, 1402-1411, 2022 | 3 | 2022 |
| Avubdi: A versatile usable big data infrastructure and its monitoring approaches for process industry S Luftensteiner, M Mayr, GC Chasparis, M Pichler Frontiers in Chemical Engineering 3, 665545, 2021 | 3 | 2021 |
| Database and Expert Systems Applications-DEXA 2024 Workshops B Moser, L Fischer, A Mashkoor, J Sametinger, AC Glock, M Mayr, ... | 3 | 2021 |
| A framework for factory-trained virtual sensor models based on censored production data S Luftensteiner, M Zwick International Conference on Database and Expert Systems Applications, 3-16, 2020 | 3 | 2020 |
| Log File Anomaly Detection Based on Process Mining Graphs S Luftensteiner, P Praher International Conference on Database and Expert Systems Applications, 383-391, 2022 | 2 | 2022 |
| Gathering Expert Knowledge in Process Industry S Luftensteiner, GC Chasparis, M Mayr Procedia Computer Science 217, 960-968, 2023 | 1 | 2023 |
| A framework for improving offline learning models with online data S Luftensteiner, M Zwick DBKDA 2021, 39, 2021 | 1 | 2021 |
| NADA: NMF-Based Anomaly Detection in Adjacency-Matrices for Industrial Machine Log-Files S Luftensteiner, P Praher, N Schwarz International Conference on Big Data Analytics and Knowledge Discovery, 369-374, 2024 | | 2024 |
| PAS-A Feature Selection Process Definition for Industrial Settings S Luftensteiner, GC Chasparis, J Küng Procedia Computer Science 232, 308-316, 2024 | | 2024 |
| Improving Virtual Sensor Models by Censored Online Data S Luftensteiner, M Zwick Procedia Computer Science 217, 938-947, 2023 | | 2023 |
| From Data to Decisions-Developing Data Analytics Use-Cases in Process Industry J Himmelbauer, M Mayr, S Luftensteiner International Conference on Database and Expert Systems Applications, 79-89, 2022 | | 2022 |
| A Synthetic Dataset for Anomaly Detection of Machine Behavior S Luftensteiner, P Praher International Conference on Database and Expert Systems Applications, 424-431, 2022 | | 2022 |
| Check for updates Filter-Based Feature Selection Methods for Industrial Sensor Data: A Review S Luftensteiner, M Mayr, G Chasparis Big Data Analytics and Knowledge Discovery: 23rd International Conference …, 2021 | | 2021 |
| Data Preprocessing and Expert Knowledge Integration for Feature Selection in Process Industry S Luftensteiner, GC Chasparis, J Kung Available at SSRN 4552873, 0 | | |
Michael MayrResearcher and Senior Data Scientist, Software Competence Center Hagenberg在 scch.at 的电子邮件经过验证
