Process mining for healthcare: Characteristics and challenges

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 …

Inferring Unobserved Events in Systems With Shared Resources and Queues

Fahland, D., Denisov, V., & van der Aalst, W. M. P. (2021). Inferring Unobserved Events in Systems With Shared Resources and Queues. Fundamenta Informaticae, 183(3-4), 203-242. https://doi.org/10.3233/FI-2021-2087 Abstract To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for Read More …

Privacy-preserving process mining in healthcare

Pika, A., Wynn, M. T., Budiono, S., ter Hofstede, A. H. M., van der Aalst, W. M. P., & Reijers, H. A. (2020). Privacy-preserving process mining in healthcare. International Journal of Environmental Research and Public Health, 17(5), [1612]. https://doi.org/10.3390/ijerph17051612 Abstract Process mining has been successfully applied in the healthcare domain and has helped to uncover Read More …

Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment

Cheng, L., van Dongen, B. F., & van der Aalst, W. M. P. (2020). Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment. IEEE Transactions on Services Computing, 13(2), 368-380. [8669858]. https://doi.org/10.1109/TSC.2019.2906203 Abstract Process descriptions are used to create products and deliver services. To lead better processes and services, the first step is Read More …

Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones

Bloemen, V., van Zelst, S., van der Aalst, W., van Dongen, B., & van de Pol, J. (Accepted/In press). Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones. Information Systems, 103, [101456]. https://doi.org/10.1016/j.is.2019.101456 Abstract Given a process model and an event log, conformance checking aims to relate the two together, e.g. to Read More …

Visualizing Token Flows Using Interactive Performance Spectra

van der Aalst, W. M. P., Tacke Genannt Unterberg, D., Denisov, V., & Fahland, D. (2020). Visualizing Token Flows Using Interactive Performance Spectra. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 369-380). (Lecture Notes in Computer Science Read More …

Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources

Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2020). Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 239-259). (Lecture Notes Read More …

Multi-dimensional performance analysis and monitoring using integrated performance spectra

Denisov, V., Fahland, D., & Van Der Aalst, W. M. P. (2020). Multi-dimensional performance analysis and monitoring using integrated performance spectra. In C. Di Ciccio (Ed.), Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020): Padua, Italy, October 4-9, 2020 (pp. 27-30). Read More …

Detecting system-level behavior leading to dynamic bottlenecks

Toosinezhad, Z., Fahland, D., Köroglu, Ö., & Van Der Aalst, W. M. P. (2020). Detecting system-level behavior leading to dynamic bottlenecks. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 17-24). [9230102] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00014 Abstract Dynamic Read More …

Mining process model descriptions of daily life through event abstraction

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining process model descriptions of daily life through event abstraction. In S. Kapoor, R. Bhatia, & Y. Bi (Eds.), Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016 (pp. 83-104). (Studies in Computational Intelligence; Read More …

Event abstraction for process mining using supervised learning techniques

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Event abstraction for process mining using supervised learning techniques. In Y. Bi, S. Kapoor, & R. Bhatia (Eds.), Proceedings of the SAI Intelligent Systems Conference (IntelliSys 2016), 21-22 September 2016, London, United Kingdom (pp. 251-269). (Lecture Notes in Networks and Systems; Read More …

Best PhD. Dissertation award at ICPM 2020 for Xixi Lu

Xixi Lu, a former PhD student of our group, has won the Best PhD. Dissertation award with her thesis “Using behavioral context in process mining: exploration, preprocessing and analysis of event data“. Her promotor was Wil van der Aalst, and Dirk Fahland was one of her copromotors.

Connecting databases with process mining: a meta model and toolset

González López de Murillas, E., Reijers, H. A., & van der Aalst, W. M. P. (2019). Connecting databases with process mining: a meta model and toolset. Software and Systems Modeling, 18(2), 1209-1247. https://doi.org/10.1007/s10270-018-0664-7 Abstract Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a Read More …

Working on Process Mining? Consider becoming a member of the IEEE Task Force on Process Mining!

If you did not join the IEEE Task Force on Process Mining yet, please consider doing so!                 >> register via https://www.tf-pm.org/subscription/form  << The IEEE Task Force on Process Mining (TFPM) was established in October 2009 as part of the IEEE Computational Intelligence Society. The set of activities and members has expanded over the last Read More …

A tour in process mining: from practice to algorithmic challenges

van der Aalst, W., Carmona, J., Chatain, T., & van Dongen, B. (2019). A tour in process mining: from practice to algorithmic challenges. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 1-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Read More …

Guided interaction exploration and performance analysis in artifact-centric process models

van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Guided interaction exploration and performance analysis in artifact-centric process models. Business and Information Systems Engineering, 61(6), 649-663. https://doi.org/10.1007/s12599-018-0546-0 Abstract Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the Read More …

Case notion discovery and recommendation: automated event log building on databases

de Murillas, E. G. L., Reijers, H. A., & van der Aalst, W. M. P. (Accepted/In press). Case notion discovery and recommendation: automated event log building on databases. Knowledge and Information Systems. https://doi.org/10.1007/s10115-019-01430-6 Abstract Process mining techniques use event logs as input. When analyzing complex databases, these event logs can be built in many ways. Read More …

Evaluating conformance measures in process mining using conformance propositions

Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 192-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Read More …

Repairing outlier behaviour in event logs

Fani Sani, M., van Zelst, S. J., & van der Aalst, W. M. P. (2018). Repairing outlier behaviour in event logs. In W. Abramowicz, & A. Paschke (Eds.), Business Information Systems – 21st International Conference, BIS 2018, Proceedings (pp. 115-131). (Lecture Notes in Business Information Processing; Vol. 320). Cham: Springer. https://doi.org/10.1007/978-3-319-93931-5_9 Abstract One of the Read More …

What if process predictions are not followed by good recommendations?

Dees, M., de Leoni, M., van der Aalst, W. M. P., & Reijers, H. A. (2019). What if process predictions are not followed by good recommendations? In J. vom Brocke , J. Mendling, & M. Rosemann (Eds.), 17th International Conference on Business Process Management 2019 Industry Forum: Proceedings of the Industry Forum at BPM 2019 Read More …

Predictive performance monitoring of material handling systems using the performance spectrum

Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2019). Predictive performance monitoring of material handling systems using the performance spectrum. In Proceedings – 2019 International Conference on Process Mining, ICPM 2019 (pp. 137-144). [8786068] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/ICPM.2019.00029 Abstract Predictive performance analysis is crucial for supporting operational Read More …

Object-centric behavioral constraint models: a hybrid model for behavioral and data perspectives

Li, G., De Carvalho, R. M., & van der Aalst, W. M. P. (2019). Object-centric behavioral constraint models: a hybrid model for behavioral and data perspectives. In Proceeding SAC ’19 Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (pp. 48-56). New York: Association for Computing Machinery, Inc. DOI: 10.1145/3297280.3297287 Abstract In order to maintain Read More …

Multi-instance mining: discovering synchronisation in artifact-centric processes

van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Multi-instance mining: discovering synchronisation in artifact-centric processes. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 18-30). (Lecture Notes in Business Information Processing; Vol. 342). Cham: Springer. DOI: Read More …

Improving merging conditions for recomposing conformance checking

Lee, W. L. J., Munoz-Gama, J., Verbeek, H. M. W., van der Aalst, W. M. P., & Sepúlveda, M. (2019). Improving merging conditions for recomposing conformance checking. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 31-43). (Lecture Notes in Business Information Read More …

Detecting behavioral design patterns from software execution data

Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2019). Detecting behavioral design patterns from software execution data. In E. Damiani, G. Spanoudakis, & L. A. Maciaszek (Eds.), Evaluation of Novel Approaches to Software Engineering – 13th International Conference, ENASE 2018, Revised Selected Papers (pp. 137-164). (Communications in Computer Read More …

Data-driven usability test scenario creation

van Eck, M. L., Markslag, E., Sidorova, N., Brosens-Kessels, A., & van der Aalst, W. M. P. (2019). Data-driven usability test scenario creation. In M. K. Lárusdóttir, M. Winckler, K. Kuusinen, P. Palanque, & C. Bogdan (Eds.), Human-Centered Software Engineering – 7th IFIP WG 13.2 International Working Conference, HCSE 2018, Revised Selected Papers (pp. 88-108). Read More …

A model-based framework to automatically generate semi-real data for evaluating data analysis techniques

Li, G., de Carvalho, R. M., & van der Aalst, W. M. P. (2019). A model-based framework to automatically generate semi-real data for evaluating data analysis techniques. In J. Filipe, A. Brodsky, M. Smialek, & S. Hammoudi (Eds.), ICEIS 2019 – Proceedings of the 21st International Conference on Enterprise Information Systems (pp. 213-220). SCITEPRESS-Science and Read More …

A general framework to identify software components from execution data

Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2019). A general framework to identify software components from execution data. In G. Spanoudakis, E. Damiani, L. Maciaszek, & L. Maciaszek (Eds.), ENASE 2019 – Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. Read More …