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  2024 (3)
Large Language Models as Knowledge Engineers. Brand, F.; Malburg, L.; and Bergmann, R. In Malburg, L., editor(s), Proceedings of the Workshops at the 32nd International Conference on Case-Based Reasoning (ICCBR-WS 2024) co-located with the 32nd International Conference on Case-Based Reasoning (ICCBR 2024), Mérida, Mexico, July 1, 2024, volume 3708, of CEUR Workshop Proceedings, pages 3–18, 2024. CEUR-WS.org.
Large Language Models as Knowledge Engineers [pdf]Paper   link   bibtex   abstract   4 downloads  
Identifying Missing Sensor Values in IoT Time Series Data: A Weight-Based Extension of Similarity Measures for Smart Manufacturing. Schultheis, A.; Malburg, L.; Grüger, J.; Weich, J.; Bertrand, Y.; Bergmann, R.; and Serral Asensio, E. In Case-Based Reasoning Research and Development - 32nd International Conference, ICCBR 2024, Merida, Mexico, July 1-4, 2024, Proceedings, volume 14775, of Lecture Notes in Computer Science, pages 240–257, 2024. Springer.
Identifying Missing Sensor Values in IoT Time Series Data: A Weight-Based Extension of Similarity Measures for Smart Manufacturing [pdf]Paper   doi   link   bibtex   abstract   4 downloads  
Exploring a Hybrid Case-Based Reasoning Approach for Time Series Adaptation in Predictive Maintenance. Schultheis, A. In Malburg, L., editor(s), Proceedings of the Workshops at the 32nd International Conference on Case-Based Reasoning (ICCBR-WS 2024) co-located with the 32nd International Conference on Case-Based Reasoning (ICCBR 2024), Merida, Mexico, July 1, 2024, volume 3708, of CEUR Workshop Proceedings, pages 230–235, 2024. CEUR-WS.org.
Exploring a Hybrid Case-Based Reasoning Approach for Time Series Adaptation in Predictive Maintenance [pdf]Paper   link   bibtex   abstract   2 downloads  
  2023 (9)
Applying MAPE-K control loops for adaptive workflow management in smart factories. Malburg, L.; Hoffmann, M.; and Bergmann, R. Journal of Intelligent Information Systems, 61(1): 83–111. 2023.
Applying MAPE-K control loops for adaptive workflow management in smart factories [pdf]Paper   doi   link   bibtex   abstract   12 downloads  
Adaptive Management of Cyber-Physical Workflows by Means of Case-Based Reasoning and Automated Planning. Malburg, L.; Brand, F.; and Bergmann, R. In Sales, T. P.; Proper, H. A.; Guizzardi, G.; Montali, M.; Maggi, F. M.; and Fonseca, C. M., editor(s), Enterprise Design, Operations, and Computing (EDOC) Workshops 2022, volume 466, of Lecture Notes in Business Information Processing, pages 79–95, 2023. Springer. The original publication is available at www.springerlink.com
Adaptive Management of Cyber-Physical Workflows by Means of Case-Based Reasoning and Automated Planning [pdf]Paper   doi   link   bibtex   abstract   15 downloads  
DataStream XES Extension: Embedding IoT Sensor Data into Extensible Event Stream Logs. Mangler, J.; Grüger, J.; Malburg, L.; Ehrendorfer, M.; Bertrand, Y.; Benzin, J.; Rinderle-Ma, S.; Serral Asensio, E.; and Bergmann, R. Future Internet, 15(3). 2023.
DataStream XES Extension: Embedding IoT Sensor Data into Extensible Event Stream Logs [pdf]Paper   doi   link   bibtex   abstract   11 downloads  
Converting semantic web services into formal planning domain descriptions to enable manufacturing process planning and scheduling in industry 4.0. Malburg, L.; Klein, P.; and Bergmann, R. Engineering Applications of Artificial Intelligence, 126: 106727. 2023.
Converting semantic web services into formal planning domain descriptions to enable manufacturing process planning and scheduling in industry 4.0 [pdf]Paper   doi   link   bibtex   abstract   5 downloads  
A framework for AI-based self-adaptive cyber-physical process systems. Guldner, A.; Hoffmann, M.; Lohr, C.; Machhamer, R.; Malburg, L.; Morgen, M.; Rodermund, S. C.; Schäfer, F.; Schaupeter, L.; Schneider, J.; Theusch, F.; Bergmann, R.; Dartmann, G.; Kuhn, N.; Naumann, S.; Timm, I. J.; Vette-Steinkamp, M.; and Weyers, B. it - Information Technology. 2023.
A framework for AI-based self-adaptive cyber-physical process systems [pdf]Paper   doi   link   bibtex   abstract   3 downloads  
IoT-enriched event log generation and quality analytics: a case study. Grüger, J.; Malburg, L.; and Bergmann, R. it - Information Technology. June 2023.
IoT-enriched event log generation and quality analytics: a case study [pdf]Paper   doi   link   bibtex   abstract   3 downloads  
Using Deep Reinforcement Learning for the Adaptation of Semantic Workflows. Brand, F.; Lott, K.; Malburg, L.; Hoffmann, M.; and Bergmann, R. In Malburg, L.; and Verma, D., editor(s), Proceedings of the Workshops at the 31st International Conference on Case-Based Reasoning (ICCBR-WS 2023) co-located with the 31st International Conference on Case-Based Reasoning (ICCBR 2023), Aberdeen, Scotland, UK, July 17, 2023, volume 3438, of CEUR Workshop Proceedings, pages 55–70, 2023. CEUR-WS.org
Using Deep Reinforcement Learning for the Adaptation of Semantic Workflows [pdf]Paper   link   bibtex   abstract   17 downloads  
Modeling and Using Complex IoT Time Series Data in Case-Based Reasoning: From Application Scenarios to Implementations. Malburg, L.; Schultheis, A.; and Bergmann, R. In Malburg, L.; and Verma, D., editor(s), Proceedings of the Workshops at the 31st International Conference on Case-Based Reasoning (ICCBR-WS 2023) co-located with the 31st International Conference on Case-Based Reasoning (ICCBR 2023), Aberdeen, Scotland, UK, July 17, 2023, volume 3438, of CEUR Workshop Proceedings, pages 81–96, 2023. CEUR-WS.org
Modeling and Using Complex IoT Time Series Data in Case-Based Reasoning: From Application Scenarios to Implementations [pdf]Paper   link   bibtex   abstract   4 downloads  
Internet of Processes and Things: A Repository for IoT-Enriched Event Logs in Smart Environments. Ehrendorfer, M.; Bertrand, Y.; Malburg, L.; Mangler, J.; Grüger, J.; Rinderle-Ma, S.; Bergmann, R.; and Asensio, E. S. In Fahland, D.; Jiménez-Ramírez, A.; Kumar, A.; Mendling, J.; Pentland, B. T.; Rinderle-Ma, S.; Slaats, T.; Versendaal, J.; Weber, B.; Weske, M.; and Winter, K., editor(s), Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Forum at BPM 2023 co-located with 21st International Conference on Business Process Management (BPM 2023), Utrecht, The Netherlands, September 11th to 15th, 2023, volume 3469, of CEUR Workshop Proceedings, pages 92–96, 2023. CEUR-WS.org
Internet of Processes and Things: A Repository for IoT-Enriched Event Logs in Smart Environments [pdf]Paper   link   bibtex   abstract  
  2022 (5)
ProGAN: Toward a Framework for Process Monitoring and Flexibility by Change via Generative Adversarial Networks. Hoffmann, M.; Malburg, L.; and Bergmann, R. In Marrella, A.; and Weber, B., editor(s), Business Process Management Workshops - BPM 2021, Rome, Italy, September 6 - 10, 2021, volume 436, of Lecture Notes in Business Information Processing, pages 43–55, 2022. Springer. The original publication is available at www.springerlink.com
ProGAN: Toward a Framework for Process Monitoring and Flexibility by Change via Generative Adversarial Networks [pdf]Paper   doi   link   bibtex   abstract   18 downloads  
SensorStream: An XES Extension for Enriching Event Logs with IoT-Sensor Data. Grüger, J.; Malburg, L.; Mangler, J.; Bertrand, Y.; Rinderle-Ma, S.; Bergmann, R.; and Serral Asensio, E. CoRR, abs/2206.11392. 2022.
SensorStream: An XES Extension for Enriching Event Logs with IoT-Sensor Data [link]Paper   link   bibtex   abstract   9 downloads  
An IoT-Enriched Event Log for Process Mining in Smart Factories. Malburg, L.; Grüger, J.; and Bergmann, R. CoRR, abs/2209.02702. 2022.
An IoT-Enriched Event Log for Process Mining in Smart Factories [link]Paper   link   bibtex   abstract   5 downloads  
Integrating process management and event processing in smart factories: A systems architecture and use cases. Seiger, R.; Malburg, L.; Weber, B.; and Bergmann, R. Journal of Manufacturing Systems, 63: 575–592. 2022.
Integrating process management and event processing in smart factories: A systems architecture and use cases [pdf]Paper   doi   link   bibtex   abstract   21 downloads  
Towards Adaptive Workflow Management by Case-Based Reasoning and Automated Planning. Malburg, L.; and Bergmann, R. In Reuss, P.; and Schönborn, J., editor(s), Workshops Proceedings for the Thirtieth International Conference on Case-Based Reasoning co-located with the Thirtieth International Conference on Case-Based Reasoning (ICCBR 2022), Nancy, France, September 12-15, 2022, volume 3389, of CEUR Workshop Proceedings, pages 211–220, 2022. CEUR-WS.org
Towards Adaptive Workflow Management by Case-Based Reasoning and Automated Planning [pdf]Paper   link   bibtex   abstract   9 downloads  
  2021 (2)
Using Expert Knowledge for Masking Irrelevant Data Streams in Siamese Networks for the Detection and Prediction of Faults. Klein, P.; Weingarz, N.; and Bergmann, R. In 2021 International Joint Conference on Neural Networks (IJCNN), 2021. Accepted for presentation.
link   bibtex   18 downloads  
Object Detection for Smart Factory Processes by Machine Learning. Malburg, L.; Rieder, M.; Seiger, R.; Klein, P.; and Bergmann, R. Procedia Computer Science, 184: 581–588. 2021. Best Paper.
Object Detection for Smart Factory Processes by Machine Learning [pdf]Paper   doi   link   bibtex   abstract   70 downloads  
  2020 (3)
Using Physical Factory Simulation Models for Business Process Management Research. Malburg, L.; Seiger, R.; Bergmann, R.; and Weber, B. In del-Río-Ortega , A.; Leopold, H.; and Santoro, F. M., editor(s), Business Process Management Workshops - BPM 2020 International Workshops, Sevilla, Spain, September 13 - 18, 2020, volume 397, of Lecture Notes in Business Information Processing, pages 95–107, 2020. Springer The original publication is available at www.springerlink.com
Using Physical Factory Simulation Models for Business Process Management Research [pdf]Paper   doi   link   bibtex   abstract   32 downloads  
Enhancing Siamese Neural Networks through Expert Knowledge for Predictive Maintenance. Klein, P.; Weingarz, N.; and Bergmann, R. In IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning, volume 1325, of Communications in Computer and Information Science, 2020. Springer International Publishing. The original publication is available at www.springerlink.com
Enhancing Siamese Neural Networks through Expert Knowledge for Predictive Maintenance [pdf]Paper   doi   link   bibtex   abstract   44 downloads  
Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0. Malburg, L.; Klein, P.; and Bergmann, R. In Panetto, H.; Madani, K.; and Smirnov, A. V., editor(s), Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2020, Budapest, Hungary, November 2-4, 2020, pages 32-43, 2020. SCITEPRESS.
Semantic Web Services for AI-Research with Physical Factory Simulation Models in Industry 4.0 [pdf]Paper   doi   link   bibtex   abstract   37 downloads  
  2019 (2)
Generation of Complex data for AI-Based Predictive Maintenance Research With a Physical Factory Model. Klein, P.; and Bergmann, R. In 16th International Conference on Informatics in Control Automation and Robotics, ICINCO 2019, Prague, Czech Republic, Proceedings , volume 1, pages 40-50, 2019. INSTICC, SciTePress.
Generation of Complex data for AI-Based Predictive Maintenance Research With a Physical Factory Model [pdf]Paper   doi   link   bibtex   18 downloads  
FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies. Klein, P.; Malburg, L.; and Bergmann, R. In Jäschke, R.; and Weidlich, M., editor(s), Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", Berlin, Germany, September 30 - October 2, 2019., volume 2454, of CEUR Workshop Proceedings, pages 253–264, 2019. CEUR-WS.org
FTOnto: A Domain Ontology for a Fischertechnik Simulation Production Factory by Reusing Existing Ontologies [pdf]Paper   link   bibtex   abstract   23 downloads  
  2018 (1)
Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance. Klein, P.; and Bergmann, R. In Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", LWDA 2018, volume 2191, pages 179–190, 2018. CEUR-WS.org
Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance [pdf]Paper   link   bibtex   abstract   17 downloads