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

Generating Event Logs with CPN IDE

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Verbeek, E., & Fahland, D. (2023). Generating Event Logs with CPN IDE. In Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 (CEUR Workshop Proceedings; Vol. 3648). Abstract This extended abstract introduces the event log generation facility of CPN IDE. CPN IDE has replaced CPN Tools as a tool Read More …

The biggest business process management problems to solve before we die

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Beerepoot, I., Di Ciccio, C., Reijers, H. A., Rinderle-Ma, S., Bandara, W., Burattin, A., Calvanese, D., Chen, T., Cohen, I., Depaire, B., Di Federico, G., Dumas, M., van Dun, C., Fehrer, T., Fischer, D. A., Gal, A., Indulska, M., Isahagian, V., Klinkmüller, C., … Zerbato, F. (2023). The biggest business process management problems to solve Read More …

The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider

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Ozkan, B., Koops, M., Türetken, O., & Reijers, H. A. (2023). The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider. Information Systems Management, 1-22. Advance online publication. https://doi.org/10.1080/10580530.2023.2286980 Abstract This study investigates the influence of Business Process Management System (BPMS) implementation on an Read More …

Online Prediction Threshold Optimization Under Semi-deferred Labelling

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Spenrath, Y., Hassani, M., & van Dongen, B. F. (2024). Online Prediction Threshold Optimization Under Semi-deferred Labelling. In T. Palpanas, & H. V. Jagadish (Eds.), 8th International workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP) (CEUR Workshop Proceedings; Vol. 3651). CEUR-WS.org. https://ceur-ws.org/Vol-3651/ Abstract In supermarket loyalty campaigns, shoppers collect stamps to redeem limited-time luxury 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 …

How well can large language models explain business processes?

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Fahland, D., Fournier, F., Limonad, L., Skarbovsky, I., & Swevels, A. J. E. (2024). How well can large language models explain business processes? arXiv, abs/2401.12846. https://doi.org/10.48550/arXiv.2401.12846 Abstract Large Language Models (LLMs) are likely to play a prominent role in future AI-augmented business process management systems (ABPMSs) catering functionalities across all system lifecycle stages. One such Read More …

Implementing Object-Centric Event Data Models in Event Knowledge Graphs

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Swevels, A., Fahland, D., & Montali, M. (2024). Implementing Object-Centric Event Data Models in Event Knowledge Graphs. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 431-443). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_33 Abstract Recent advances in object-centric process Read More …

Multi-perspective Conformance Checking: Identifying and Understanding Patterns of Anomalous Behavior

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Mozafari Mehr, A. S. (2024). Multi-perspective Conformance Checking: Identifying and Understanding Patterns of Anomalous Behavior. [Phd Thesis 1 (Research TU/e / Graduation TU/e), Mathematics and Computer Science]. Eindhoven University of Technology. Summary The problem of anomaly detection in business process executions has high level of complexity. On one hand, detecting deviating behavior requires considering various Read More …

Using Machine Learning Techniques to Support the Emergency Department

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van Delft, R. A. J. J., & de Carvalho, R. M. (2022). Using Machine Learning Techniques to Support the Emergency Department. Computing and Informatics, 41(1), 154-171. https://doi.org/10.31577/CAI_2022_1_154 Abstract This research lays down foundations for a stronger presence of machine learning in the emergency department. Using machine learning to make predictions on a patient’s situation can Read More …

From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests

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Verdaasdonk, M. J. A., & de Carvalho, R. M. (2022). From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests. Healthcare Analytics, 2, Article 100040. https://doi.org/10.1016/j.health.2022.100040 Abstract One of the goals to improve the quality of care in hospitals is to set a maximum of four hours Read More …

Domain engineering for customer experience management

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Benzarti, I., Mili, H., Medeiros de Carvalho, R., & Leshob, A. (2022). Domain engineering for customer experience management. Innovations in Systems and Software Engineering, 18(1), 171-191. https://doi.org/10.1007/s11334-021-00426-2 Abstract Customer experience management (CXM) denotes a set of practices, processes, and tools, that aim at personalizing a customer’s interactions with a company around the customer’s needs and Read More …

An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence

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de Carvalho, R. M., Nguyen, H., Heetveld, M., & Luime, J. (2022). An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence. In T. X. Bui (Ed.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 (pp. 4108-4117). IEEE Computer Society. Abstract The effects of Read More …

Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction

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Bekelaar, J. W. R., Luime, J. J., & de Carvalho, R. M. (2023). Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 378-390). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_28 Read More …

Identifying the Context of Data Usage to Diagnose Privacy Issues through Process Mining

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Mehr, A. S. M., de Carvalho, R. M., & van Dongen, B. (2023). Identifying the Context of Data Usage to Diagnose Privacy Issues through Process Mining. Transactions on Data Privacy, 16(2), 123-151. http://www.tdp.cat/issues21/tdp.a456a22.pdf Abstract In recent years, data privacy issues are increasingly concerned by organisations and gov-ernments. Organisations often define a set of rules as Read More …

Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems

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Lo Bianco, R., Dijkman, R. M., Nuijten, W. P. M., & van Jaarsveld, W. L. (2023). Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Read More …

Analytical Problem Solving Based on Causal, Correlational and Deductive Models

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de Mast, J., Steiner, S., Nuijten, W. P. M., & Kapitan, D. (2023). Analytical Problem Solving Based on Causal, Correlational and Deductive Models. American Statistician, 77(1), 51-61. https://doi.org/10.1080/00031305.2021.2023633 Abstract Many approaches for solving problems in business and industry are based on analytics and statistical modeling. Analytical problem solving is driven by the modeling of relationships Read More …

Scheduling a Real-World Photolithography Area with Constraint Programming

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Deenen, P. C., Nuijten, W. P. M., & Akcay, A. (2023). Scheduling a Real-World Photolithography Area with Constraint Programming. IEEE Transactions on Semiconductor Manufacturing, 36(4), 590-598. Article 10214506. https://doi.org/10.1109/TSM.2023.3304517 Abstract This paper studies the problem of scheduling machines in the photolithography area of a semiconductor manufacturing facility. The scheduling problem is characterized as an unrelated Read More …

Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts

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Reijnen, R., Zhang, Y., Nuijten, W. P. M., Senaras, C., & Goldak, M. (2021). Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020) (pp. 2647-2654). Article 9308584 IEEE Press. https://doi.org/10.1109/SSCI47803.2020.9308584 Abstract A multi-agent path finding (MAPF) problem is concerned Read More …

Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction

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Karetnikov, A., Nuijten, W., & Hassani, M. (2021). Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction. In P. Pezarat-Correia, J. Vilas-Boas, & J. Cabri (Eds.), icSPORTS 2021 – Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (pp. 43-53). SciTePress Digital Library. Abstract In individual sports, the judgment Read More …

Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems

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Mertens, T., & Hassani, M. (2023). Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems. In M.-R. Amini, S. Canu, A. Fischer, T. Guns, P. Kralj Novak, & G. Tsoumakas (Eds.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part VI Read More …

Conformance checking of process event streams with constraints on data retention

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Zaman, R., Hassani, M., & van Dongen, B. F. (2023). Conformance checking of process event streams with constraints on data retention. Information Systems, 117, Article 102228. https://doi.org/10.1016/j.is.2023.102228 Abstract Conformance checking (CC) techniques in process mining determine the conformity of cases, by means of their event sequences, with respect to a business process model. Online conformance Read More …

Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings

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Wolters, L., & Hassani, M. (2023). Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 145-157). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). https://doi.org/10.1007/978-3-031-27815-0_11 Abstract Customer journey analysis Read More …

PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees.

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Huete, J., Qahtan, A. A., & Hassani, M. (2023). PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees. In H. Shahriar, Y. Teranishi, A. Cuzzocrea, M. Sharmin, D. Towey, AKM. J. A. Majumder, H. Kashiwazaki, J.-J. Yang, M. Takemoto, N. Sakib, R. Banno, & S. I. Ahamed (Eds.), COMPSAC (pp. 328-333) https://doi.org/10.1109/COMPSAC57700.2023.00051 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 …

Supervised learning of process discovery techniques using graph neural networks

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Sommers, D., Menkovski, V., & Fahland, D. (2023). Supervised learning of process discovery techniques using graph neural networks. Information Systems, 115, Article 102209. https://doi.org/10.1016/j.is.2023.102209 Abstract Automatically discovering a process model from an event log is the prime problem in process mining. This task is so far approached as an unsupervised learning problem through graph synthesis Read More …

Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs

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Swevels, A., Dijkman, R. M., & Fahland, D. (2023). Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Proceedings (pp. 180-197). (Lecture Notes in Computer Science (LNCS); Vol. Read More …

AI-augmented Business Process Management Systems: A Research Manifesto

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Dumas, M., Fournier, F., Limonad, L., Marrella, A., Montali, M., Rehse, J. R., Accorsi, R., Calvanese, D., De Giacomo, G., Fahland, D., Gal, A., La Rosa, M., Völzer, H., & Weber, I. (2023). AI-augmented Business Process Management Systems: A Research Manifesto. ACM Transactions on Management Information Systems, 14(1), Article 11. https://doi.org/10.1145/3576047 Abstract AI-augmented Business Process Read More …

Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach

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Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2023). Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 44-56). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Read More …

An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns

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Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2022). An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns. In W. Chen, L. Yao, T. Cai, S. Pan, T. Shen, & X. Li (Eds.), Advanced Data Mining and Applications – 18th International Conference, ADMA 2022, Proceedings (pp. 397-412). (Lecture Notes in Computer Read More …

MLA: A Tool for Multi-Perspective Conformance Checking of Business Processes

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Mehr, A. S. M., de Carvalho, R. M., & van Dongen, B. (2021). MLA: A Tool for Multi-Perspective Conformance Checking of Business Processes. In ICPM 2021 Doctoral Consortium and Demo Track 2021 (pp. 35-36). (CEUR Workshop Proceedings; Vol. 3098). CEUR-WS.org. https://ceur-ws.org/Vol-3098/demo_200.pdf Abstract Existing conformance checking techniques focus more on the control-flow perspective rather than other Read More …

Aligning Event Logs to Resource-Constrained ν-Petri Nets

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Sommers, D., Sidorova, N., & van Dongen, B. (2022). Aligning Event Logs to Resource-Constrained ν-Petri Nets. In L. Bernardinello, & L. Petrucci (Eds.), Application and Theory of Petri Nets and Concurrency – 43rd International Conference, PETRI NETS 2022, Proceedings (pp. 325-345). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More …