ProM 6.11 released

Today, October 13th, 2021, ProM 6.11 has been released. The framework of ProM 6.11 fixes a bug that resulted in an attempt to show a modal dialog even when using the (headless) CLI context. New packages in ProM 6.11 AdvancedEventLogFiltering 6.11.38, by Daniel Tacke genannt Unterberg CounterfactualExplanation 6.11.8, by Mahnaz Qafari ERPSimulator 6.11.1, by Gyunam Read More …

Predicting Next Touch Point In A Customer Journey – A Use Case In Telecommunication

Hassani, M., & Habets, S. (2021). Predicting Next Touch Point In A Customer Journey – A Use Case In Telecommunication. In 35th ECMS INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION (1 ed., Vol. 35, pp. 48-54). (Proceedings – European Council for Modelling and Simulation, ECMS). https://doi.org/10.7148/2021-0048 Abstract Customer journey analysis is rapidly increasing in popularity, as Read More …

Privacy and Confidentiality in Process Mining – Threats and Research Challenges

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

Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs. In BPM (Forum) (pp. 212-229) https://doi.org/10.5281/zenodo.5091610, https://doi.org/10.1007/978-3-030-85440-9_13 Abstract Business process management organizes work into several interrelated “units of work”, fundamentally conceptualized as a task. The classical concept of a task as a single step Read More …

Closing the process mining circle with CPN IDE

CPN Tools is a tool that is well-known in the Petri net community. CPN Tools provides a mature environment for constructing, simulating, and performing analysis of CPN (Coloured Petri Net) models. CPN Tools consists of an ML-based CPN simulator (the back-end), and a CPN editor (the front-end) that has been developed in the BETA programming Read More …

Predicting the need of Nursing or Care Home and Home Care

(Verpleeg- en Verzorgingshuizen en Thuiszorg (VVT) in Dutch)  The St. Antonius hospital in Nieuwegein is an ambitious top clinical training hospital. Every year, more than 40,000 patients are admitted, of which 6,000 patients go home through Care Mediation with home care or to a nursing or care home. This outflow is very erratic with seasonal influences. At Read More …

Process discovery using in-database minimum self distance abstractions

Syamsiyah, A., & Leemans, S. J. J. (2020). Process discovery using in-database minimum self distance abstractions. In 35th Annual ACM Symposium on Applied Computing, SAC 2020 (pp. 26-35). Association for Computing Machinery, Inc. https://doi.org/10.1145/3341105.3373846 Abstract Process executions generate event data that are typically stored in legacy information systems, such as databases. However, process discovery, which Read More …

The Log Skeleton Visualizer in ProM 6.9

Verbeek, H.M.W. The Log Skeleton Visualizer in ProM 6.9. Int J Softw Tools Technol Transfer (2021). https://doi.org/10.1007/s10009-021-00618-y Abstract Process discovery is an important area in the field of process mining. To help advance this area, a process discovery contest (PDC) has been set up, which allows us to compare different approaches. At the moment of Read More …

Explainable Industrial Optimizers

DELMIA Quintiq develops widely used optimizers providing high-quality solutions across a breadth of industries. Human planners, as users of the optimizers, possess substantial soft knowledge, which is often difficult or expensive to capture in mathematical optimization algorithms. The aim of the Explainable Industrial Optimizers project is to promote cooperative planning by the human users and Read More …

Lecturer Process Analytics

The process analytics research group of the department of Mathematics and Computer Science at Eindhoven University of Technology is looking for a fulltime or parttime lecturer. Position Non academic staff (supporting staff) Department(s) Department of Mathematics & Computer Science FTE 1,0 Date off 13/06/2021 Reference number V32.5007 Job description The small research group of Process Read More …

Business Process Management: The evolution of a discipline

Reijers, H. A. (2021). Business Process Management: The evolution of a discipline. Computers in Industry, 126, [103404]. https://doi.org/10.1016/j.compind.2021.103404 Abstract Business Process Management (BPM) embodies a management philosophy, which is supported by a range of methods, techniques, and tools. Academics are continuously expanding this repertoire. In this overview article, the themes are sketched that characterize the Read More …

Process training for industrial organisations using 3D environments: An empirical analysis

Leyer, M., Aysolmaz, B., Brown, R., Türkay, S., & Reijers, H. A. (2021). Process training for industrial organisations using 3D environments: An empirical analysis. Computers in Industry, 124, [103346]. https://doi.org/10.1016/j.compind.2020.103346 Abstract Industrial organisations spend considerable resources on training employees with respect to the organisations’ business processes. These resources include business process models, diagrams depicting vital Read More …

Efficient process conformance checking on the basis of uncertain event-to-activity mappings

van der Aa, H., Leopold, H., & Reijers, H. A. (2020). Efficient process conformance checking on the basis of uncertain event-to-activity mappings. IEEE Transactions on Knowledge and Data Engineering, 32(5), 927-940. [8634941]. https://doi.org/10.1109/TKDE.2019.2897557 Abstract Conformance checking enables organizations to automatically identify compliance violations based on the analysis of observed event data. A crucial requirement 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 …

Working around health information systems: To accept or not to accept?

Beerepoot, I., Ouali, A., van de Weerd, I., & Reijers, H. A. (2020). Working around health information systems: To accept or not to accept? In J. vom Brocke, S. Gregor, & O. Muller (Eds.), 27th European Conference on Information Systems – Information Systems for a Sharing Society, ECIS 2019 [182] Association for Information Systems. https://aisel.aisnet.org/ecis2019_rp/182 Read More …

Selecting a process variant modeling approach: guidelines and application

Aysolmaz, B., Schunselaar, D. M. M., Reijers, H. A., & Yaldiz, A. (2019). Selecting a process variant modeling approach: guidelines and application. Software and Systems Modeling, 18(2), 1155-1178. https://doi.org/10.1007/s10270-017-0648-z Abstract Various modeling approaches have been introduced to manage process diversity in a business context. For practitioners, it is difficult to select an approach suitable for Read More …

The potential of workarounds for improving processes

Beerepoot, I., van de Weerd, I., & Reijers, H. A. (2019). The potential of workarounds for improving processes. In C. Di Francescomarino, R. Dijkman, & U. Zdun (Eds.), Business Process Management Workshops – BPM 2019 International Workshops, Revised Selected Papers (pp. 338-350). (Lecture Notes in Business Information Processing; Vol. 362 LNBIP). Springer. https://doi.org/10.1007/978-3-030-37453-2_28 Abstract Several 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 …

Enabling efficient process mining on large data sets: realizing an in-database process mining operator

Dijkman, R., Gao, J., Syamsiyah, A., van Dongen, B., Grefen, P., & ter Hofstede, A. (2020). Enabling efficient process mining on large data sets: realizing an in-database process mining operator. Distributed and Parallel Databases, 38(1), 227-253. https://doi.org/10.1007/s10619-019-07270-1 Abstract Process mining can be used to analyze business processes based on logs of their execution. These execution 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, XX(XX), [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 …

Using graph data structures for event logs

Esser, S., & Fahland, D. (2019). Using graph data structures for event logs. https://doi.org/10.5281/zenodo.3333831 Abstract Process mining as described in by Wil van der Aalst in is a combination of data mining and business process management to a new discipline. The general purpose of process mining is to derive process insights from event data captured 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 …

Scalable alignment of process models and event logs: An approach based on automata and S-components

Reißner, D., Armas-Cervantes, A., Conforti, R., Dumas, M., Fahland, D., & La Rosa, M. (2020). Scalable alignment of process models and event logs: An approach based on automata and S-components. Information Systems, 94, [101561]. https://doi.org/10.1016/j.is.2020.101561 Abstract Given a model of the expected behavior of a business process and given an event log recording its observed 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 …

Identifying and reducing errors in remaining time prediction due to inter-case dynamics

Klijn, E. L., & Fahland, D. (2020). Identifying and reducing errors in remaining time prediction due to inter-case dynamics. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 25-32). [9229927] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00015 Abstract Remaining time prediction 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 …

Defining meaningful local process models

Brunings, M., Fahland, D., & van Dongen, B. (2020). Defining meaningful local process models. In W. van der Aalst, R. Bergenthum, & J. Carmona (Eds.), ATAED 2020 Algorithms & Theories for the Analysis of Event Data 2020: Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data 2020: Satellite event Read More …

Log skeletons: a classification approach to process discovery

Verbeek, H. M. W., & Medeiros de Carvalho, R. (2018). Log skeletons: a classification approach to process discovery. arXiv.org. http://arxiv.org/abs/1806.08247 Abstract To test the effectiveness of process discovery algorithms, a Process Discovery Contest (PDC) has been set up. This PDC uses a classification approach to measure this effectiveness: The better the discovered model can classify 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 …

Run 13 of “Introduction to Process Mining with ProM” MOOC started on February 1, 2021

On February 1, 2021, the thirteenth run of the free FutureLearn online course ‘Introduction to process mining with ProM’ will start. Join the 17.000 students who enrolled before you and join the course! Process mining is a novel collection of techniques that connects the areas of data science and business process management. Using process mining Read More …

Run 7 of “Process Mining in Healthcare” MOOC started on February 1, 2021

On February 1, 2021, the seventh run of the free FutureLearn online course ‘Process mining in healthcare’ will start, register now! We are happy to be able to run this course again, after more than 3500 students registered for the first six runs. Healthcare in particular has come under increasing pressure to reduce cost while Read More …

Data Minimisation as Privacy and Trust Instrument in Business Processes

Zaman, R., Hassani, M., & van Dongen, B. F. (Accepted/In press). Data Minimisation as Privacy and Trust Instrument in Business Processes. In Business Process Management Workshops (BPM 2020) Springer. Abstract Data is vital for almost all sorts of business processes and workflows. However, the possession of personal data of other beings bear consequences. Data is Read More …