Tag: Felix Mannhardt

  • Felix Mannhardt - Position: UD Room: MF 7.119 Tel (internal): 3425 Links: CoursesExternal assignmentsAssignmentsPresentationsProjectsPublications External links: Personal home pageGoogle scholar pageScopus pageORCID pageDBLP pageTU/e page Awards Recent courses Recent external assignments Recent assignments Recent presentations Recent projects Recent publications

Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper

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Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2024). Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 296-308). (Lecture Notes in Business Information Processing; Vol. Read More …

Comparing Conformance Checking for Decision Mining: An Axiomatic Approach

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Banham, A., ter Hofstede, A. H. M., Leemans, S. J. J., Mannhardt, F., Andrews, R., & Wynn, M. T. (2024). Comparing Conformance Checking for Decision Mining: An Axiomatic Approach. IEEE Access, 12, 60276-60298. Article 10504896. https://doi.org/10.1109/ACCESS.2024.3391234 Abstract Process mining uses historical executions of business processes (as recorded in an event log) to uncover and describe Read More …

Customer journeys and process mining – challenges and opportunities

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Halvorsrud, R., Mannhardt, F., Prillard, O., & Boletsis, C. (2024). Customer journeys and process mining – challenges and opportunities. In International Conference on Exploring Service Science (IESS 2.4) (Vol. 62, pp. 05002). (ITM Web of Conferences). https://doi.org/10.1051/itmconf/20246205002

Experience-Based Resource Allocation for Remaining Time Optimization

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Padella, A., Mannhardt, F., Vinci, F., De Leoni, M., & Vanderfeesten, I. (2024). Experience-Based Resource Allocation for Remaining Time Optimization. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (Eds.), Business Process Management: 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Proceedings (pp. 345-362). Article Chapter 20 (Lecture Notes in Computer Science (LNCS); Read More …

The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace

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Mannhardt, F., Halvorsrud, R., Meironas, O., & Brurok, L. (2024). The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace. In Business Process Management: Blockchain, Robotic Process Automation, Central and Eastern European, Educators and Industry Forum (Vol. 527, pp. 451-461). Article Chapter 33 (Lecture Notes in Business Information Processing; Vol. 527). https://doi.org/10.1007/978-3-031-70445-1_33

Fundamentals of Process Mining (JBI060) 2024-2025

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Objectives The main learning objective of FPM is to be able to understand the relation between sequential multi-variate event data and processes and, ultimately, to learn how to properly apply data science methods in the context of processes. Specifically, the following learning objectives are intended:  to be able to identify challenges and requirements for using Read More …

Seminar Process Analytics (2IMI00) 2024-2025

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Objectives This seminar combines teaching research methods (in preparation for a Master project) with providing students with recent and ongoing research in the area of event data analysis and process analysis. We study recent research articles, book chapters, and Master theses on topics along the entire analysis life-cycle. Through presentation and group discussions, we work Read More …

Advanced Process Mining (2AMI20) 2024-2025

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Objectives After taking this course students should be able to: have a detailed understanding of the entire process mining spectrum and the methodology for process mining analysis can derive and pre-process event logs from raw data and have understand and can work with a specialized form of event data such as event knowledge graphs, or Read More …

Data Challenge 3 (JBG060) 2024-2025

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Objectives Non Bachelor Data Science wanting to register for this course should reach out to program management via mcs.academic.advisor.bds@tue.nl for formal approval After taking this course students should be able to independently: recognize the phases of data analytics research and divide the research process in these phases familiarize themselves with techniques to understand a complex dataset Read More …

Multi-Perspective Concept Drift Detection: Including the Actor Perspective

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Klijn, E. L., Mannhardt, F., & Fahland, D. (2024). Multi-perspective Concept Drift Detection: Including the Actor Perspective. In G. Guizzardi, F. Santoro, H. Mouratidis, & P. Soffer (Eds.), Advanced Information Systems Engineering – 36th International Conference, CAiSE 2024, Proceedings (pp. 141-157). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More …

Event Knowledge Graphs for Auditing: A Case Study

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Klijn, E. L., Preuss, D., Imeri, L., Baumann, F., Mannhardt, F., & Fahland, D. (2024). Event Knowledge Graphs for Auditing: A Case Study. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 84-97). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_7 Read More …

An Experiment on Transfer Learning for Suffix Prediction on Event Logs

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van Luijken, M., Ketykó, I., & Mannhardt, F. (2024). An Experiment on Transfer Learning for Suffix Prediction on Event Logs. In J. De Weerdt, & L. Pufahl (Eds.), Business Process Management Workshops – BPM 2023 International Workshops, Utrecht, The Netherlands, September 11–15, 2023, Revised Selected Papers (pp. 31-43). (Lecture Notes in Business Information Processing; Vol. 492 LNBIP). Springer. Read More …

Seminar Process Analytics (2IMI00) 2023

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This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …

Data Challenge 3 (JBG060) 2023

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The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses. Data Challenge 3 is the final course in this series and shall familiarize students with the skills of designing and Read More …

DBL Process mining (2IOI0) 2023

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In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics Read More …

Advanced Process Mining (2AMI20) 2023

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Many real-life phenomena studied with Data Science methods unfold over time. They often involve many people, objects, agents, machines, entities, etc. that interact with each other while distributed in time and space. Such dynamics are called processes and are present everywhere: in software systems medical treatments, logistics systems, manufacturing, and even entire organizations. Process mining Read More …

Aggregating Event Knowledge Graphs for Task Analysis

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Klijn, E. L., Mannhardt, F., & Fahland, D. (2023). Aggregating Event Knowledge Graphs for Task Analysis. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 493-505). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_36 Abstract Aggregation of event data is a Read More …

Building User Journey Games from Multi-party Event Logs

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Kobialka, P., Mannhardt, F., Tapia Tarifa, S. L., & Johnsen, E. B. (2023). Building User Journey Games from Multi-party Event Logs. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 71-83). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_6 Abstract To Read More …

Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study

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Dubbeldam, A. L., Ketykó, I., de Carvalho, R. M., & Mannhardt, F. (2023). Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 366-377). (Lecture Notes in Business Information Processing; Read More …

Exploring Task Execution Patterns in Event Graphs

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Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Exploring Task Execution Patterns in Event Graphs. In M. Jans, G. Janssenswillen, A. Kalenkova , & F. M. Maggi (Eds.), ICPM 2021 Doctoral Consortium and Demo Track 2021: Proceedings of the ICPM Doctoral Consortium and Demo Track 2021 co-located with 10th International Conference on Process Mining Read More …

Discovering Care Pathways for Multi-morbid Patients Using Event Graphs

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Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2022). Discovering Care Pathways for Multi-morbid Patients Using Event Graphs. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers. (pp. 352-364). (Lecture Notes in Business Information Processing (LNBIP); Read More …

Privacy and Confidentiality in Process Mining: Threats and Research Challenges

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Elkoumy, G., Fahrenkrog-Petersen, S. A., Sani, M. F., Koschmider, A., Mannhardt, F., Voigt, S. N. V., Rafiei, M., & Waldthausen, L. V. (2022). Privacy and Confidentiality in Process Mining: Threats and Research Challenges. ACM Transactions on Management Information Systems, 13(1), [11]. https://doi.org/10.1145/3468877 Abstract Privacy and confidentiality are very important prerequisites for applying process mining to Read More …

Quantifying the Re-identification Risk in Published Process Models

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Maatouk, K., & Mannhardt, F. (2022). Quantifying the Re-identification Risk in Published Process Models. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers (Vol. 433, pp. 382-394). (Lecture Notes in Business Information Processing (LNBIP)). Springer. https://doi.org/10.1007/978-3-030-98581-3_28 Abstract Read More …

Responsible Process Mining

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Mannhardt, F. (2022). Responsible Process Mining. In W. M. P. van der Aalst, & J. Carmona (Eds.), Process Mining Handbook (pp. 373-401). (Lecture Notes in Business Information Processing; Vol. 448). Springer. https://doi.org/10.1007/978-3-031-08848-3_12 Abstract The prospect of data misuse negatively affecting our life has lead to the concept of responsible data science. It advocates for responsibility Read More …

Seminar Process Analytics (2IMI00) 2022

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This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …

DBL Process mining (2IOI0) 2022

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In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics Read More …

Advanced Process Mining (2AMI20) 2022

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Many real-life phenomena studied with Data Science methods unfold over time. They often involve many people, objectes, agents, machines, entites, etc. that interact with each other while distributed in time and space. Such dynamics are called processes and are present everywhere: in software systems medical treatments, logistics systems, manufacturing, and even entire organizations. Process mining Read More …

Event Granularity in User Journeys

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Context This project is defined in the scope of the Smart Journey Mining project [1, 9]. The SJM project vision is to increase the quality of services by uniting research on customer journeys and process mining using new developments in logic-based analysis and artificial intelligence. Research in SJM is done together with SINTEF Digital (Norway), Read More …

Privacy Guarantees in Process Discovery

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Responsible Process Mining as a topic is introduced in [1]: “The prospect of data misuses negatively affecting our life has led to the concept of responsible data science. It advocates for responsibility to be built, by design, into data management, data analysis, and algorithmic decision-making techniques such that it is made difficult or even impossible Read More …

Process mining for healthcare: Characteristics and challenges

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Jorge Munoz-gama, Niels Martin, Carlos Fernandez-llatas, Owen A. Johnson, Marcos Sepúlveda, Emmanuel Helm, Victor Galvez-yanjari, Eric Rojas, Antonio Martinez-millana, Davide Aloini, Ilaria Angela Amantea, Robert Andrews, Michael Arias, Iris Beerepoot, Elisabetta Benevento, Andrea Burattin, Daniel Capurro, Josep Carmona, Marco Comuzzi, Benjamin Dalmas, Rene De La Fuente, Chiara Di Francescomarino, Claudio Di Ciccio, Roberto Gatta, Chiara Read More …

Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions

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Koorn, J. J., Lu, X., Mannhardt, F., Leopold, H., & Reijers, H. A. (2022). Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions. https://doi.org/10.24251/HICSS.2022.503 Abstract Process mining is a family of techniques that can aid healthcare organizations in improving their processes. Most existing process mining techniques do not provide insights Read More …

What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning

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Ketykó, I., Mannhardt, F., Hassani, M., & van Dongen, B. F. (2021). What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning. CoRR, abs/2110.10225. https://arxiv.org/abs/2110.10225 Abstract Deep Learning is proven to be an effective tool for modeling sequential data as shown by the success in Natural Language, Computer Vision and Signal Read More …

Privacy and Confidentiality in Process Mining – Threats and Research Challenges

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Elkoumy, G., Fahrenkrog-Petersen, S. A., Sani, M. F., Koschmider, A., Mannhardt, F., Voigt, S. N. V., Rafiei, M., & Waldthausen, L. V. (Accepted/In press). Privacy and Confidentiality in Process Mining – Threats and Research Challenges. ACM Transactions on Management Information Systems, XX(X). https://arxiv.org/abs/2106.00388 Abstract Privacy and confidentiality are very important prerequisites for applying process mining Read More …

Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs

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Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs. In A. Polyvyanyy, M. T. Wynn, A. Van Looy, & M. Reichert (Eds.), Business Process Management Forum, BPM 2021, Proceedings (pp. 212-229). (Lecture Notes in Business Information Processing; Vol. 427 LNBIP). https://doi.org/10.5281/zenodo.5091610, https://doi.org/10.1007/978-3-030-85440-9_13 Abstract Business Read More …

Detection of batch activities from event logs

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Martin, N., Pufahl, L., & Mannhardt, F. (2021). Detection of batch activities from event logs. Information Systems, 95, [101642]. https://doi.org/10.1016/j.is.2020.101642 Abstract Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this Read More …

Designing a Privacy Dashboard for a Smart Manufacturing Environment

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Mannhardt, F., Oliveira, M., & Petersen, S. A. (2020). Designing a Privacy Dashboard for a Smart Manufacturing Environment. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century – I3E 2019 IFIP WG 6.11 International Read More …

Event abstraction in process mining: literature review and taxonomy

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van Zelst, S. J., Mannhardt, F., de Leoni, M., & Koschmider, A. (2020). Event abstraction in process mining: literature review and taxonomy. Granular Computing, XX(XX). https://doi.org/10.1007/s41066-020-00226-2 Abstract The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., Read More …