Brunings, M., Fahland, D., & Verbeek, E. (2022). Discover Context-Rich Local Process Models (Extended Abstract). In M. Hassani, A. Koschmider, M. Comuzzi, F. M. Maggi, & L. Pufahl (Eds.), ICPM 2022 Doctoral Consortium and Demo Track 2022: Proceedings of the ICPM Doctoral Consortium and Demo Track 2022 (ICPM-D 2022), Bolzano, Italy, October, 2022 (pp. 100-103). Read More …
Description The AUTO-TWIN project addresses the technological shortcoming and economic liability of the development and usage of digital twins that are accepted as the accelerator and enabler of Circular Economy in businesses and production by conduction research in 3 areas: introducing a breakthrough method for automated process-aware discovery towards autonomous Digital Twins generation, to support Read More …
Verbeek, E., & Fahland, D. (2021). CPN IDE: An Extensible Replacement for CPN Tools That Uses Access/CPN. 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 Read More …
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 …
Do you believe you have implemented a good discovery algorithm? Then submit it to the PDC 2021 to put it to the test! If you submit your implemented discovery algorithm to the PDC 2021, and if your algorithm scores best on our data set of 480 training logs, then you win the contest! The contest Read More …
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 …
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based Read More …
Dixit, P. A. M. (2019). Interactive process mining Eindhoven: Technische Universiteit Eindhoven
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 …
The Block Layout can be used to create a layout for a process graph. For this, it uses well-known Petri-net-based reduction rules to reduce the entire net into a single place. For nicely structured process graphs, this layout works quite well, but for more complex structured graphs, the resulting layout needs to be improved. Either Read More …
On April 1, 2019, the tenth run of the free FutureLearn online course ‘Introduction to process mining with ProM’ will start. Join the 13.000 students who enrolled before you and join the course now! Process mining is a novel collection of techniques that connects the areas of data science and business process management. Using process Read More …
Dixit, Prabhakar M., Verbeek, H.M.W. & van der Aalst, Wil M.P. (2018). Incremental computation of synthesis rules for free-choice Petri nets. In Peter Csaba Ölveczky & Kyungmin Bae (Eds.), Formal Aspects of Component Software – 15th International Conference, FACS 2018, Proceedings (pp. 97-117). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence Read More …
Dixit, P. M., Verbeek, H.M.W., Buijs, J. C.A.M. & van der Aalst, W. M.P. (2018). Interactive data-driven process model construction. In Xiaoyong Du, Guoliang Li, Zhanhuai Li, Juan C. Trujillo, Tok Wang Ling, Karen C. Davis & Mong Li Lee (Eds.), Conceptual Modeling – 37th International Conference, ER 2018, Proceedings (pp. 251-265). (Lecture Notes in Read More …
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Dixit, P.M., Buijs, J.C.A.M., Verbeek, H.M.W., & van der Aalst, W.M.P. (2018). Fast incremental conformance analysis for interactive process discovery. In W. Abramowicz & A. Paschke (Eds.), Business Information Systems – 21st International Conference, BIS 2018, Proceedings (pp. 163-175). (Lecture Notes in Business Information Processing, No. 320). Springer. Abstract Interactive process discovery allows users to Read More …
Lee, Wai Lam Jonathan, Verbeek, H.M.W., Munoz-Gama, Jorge, van der Aalst, Wil M.P. & Sepúlveda, Marcos (2018). Recomposing conformance : Closing the circle on decomposed alignment-based conformance checking in process mining. Information Sciences, 466, 55-91. Abstract In the area of process mining, efficient conformance checking is one of the main challenges. Several process mining vendors Read More …
Sonke, Willem, Verbeek, Kevin, Meulemans, Wouter, Verbeek, Eric & Speckmann, Bettina (2018). Optimal algorithms for compact linear layouts. Proceedings – 2018 IEEE Pacific Visualization Symposium, PacificVis 2018 (pp. 1-10). Brussels: IEEE Computer Society. Abstract Linear layouts are a simple and natural way to draw a graph: all vertices are placed on a single line and Read More …
Meulemans, W., Sonke, W.M., Speckmann, B., Verbeek, H.M.W. & Verbeek, K.A.B. (2018). Optimal algorithms for compact linear layouts. Abstracts of the 34th European Workshop on Computational Geometry (EuroCG), 21-23 March 2018, Berlin, Germany (pp. 10:1-10:6). Abstract Linear layouts are a simple and natural way to draw a graph: all vertices are placed on a single Read More …
Garcia Caballero, Humberto S., Westenberg, Michel A., Verbeek, H.M.W. & van der Aalst, Wil M.P. (2018). Visual analytics for soundness verification of process models. In M. Weidlich & E. Teniente (Eds.), Business Process Management Workshops (pp. 744-756). (Lecture Notes in Business Information Processing, No. 308). Dordrecht: Springer Netherlands. Abstract Soundness validation of process models is Read More …
van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P. && Verbeek, H.M.W. (2018). Discovering workflow nets using integer linear programming. Computing, 100(5), 529-556. Abstract Process mining is concerned with the analysis, understanding and improvement of business processes. Process discovery, i.e. discovering a process model based on an event log, is considered the most challenging Read More …
Business Process Re-engineering for General Data Protection Regulation Description The goal of BPR4GDPR is to provide a holistic framework able to support end-to-end GDPR-compliant intra- and interorganisational ICT-enabled processes at various scales, while also being generic enough, fulfilling operational requirements covering diverse application domains. To this end, proposed solutions will have a strong semantic foundation Read More …
Description The Data Science Centre Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data and the need for data & process scientists (http://www.tue.nl/dsce/). The DSC/e has recently started a long-term strategic cooperation with Philips Research Eindhoven on three topics: data science, health and lighting. As a first concrete action, 70 PhD Read More …
Eric is the scientific programmer in the PA group. As such, he is the custodian of the process mining framework ProM. In you want access to the ProM repository, or have any questions related to ProM and its development, as Eric. Recently, he has been working on a decomposition framework for both process discovery as Read More …
Article Scientific peer reviewed Arriagada-Benítez, M., Sepúlveda, M., Munoz-Gama, J. & Buijs, J.C.A.M. (2017). Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences, 7(10):1023. Bolt, A., de Leoni, M. & van der Aalst, W.M.P. (2017). Process variant comparison: using event logs to detect differences in behavior Read More …
Article Scientific peer reviewed Van Der Aa, Han, Leopold, H. & Reijers, H.A. (2016). Dealing with behavioral ambiguity in textual process descriptions. Lecture notes in computer science, 9850, 271-288. Scopus. van der Aa, J.H., Reijers, H.A. & Vanderfeesten, I.T.P. (2016). Designing like a pro : the automated composition of workflow activities. Computers in Industry, 75, Read More …
Article Scientific peer reviewed Adriansyah, Arya, Munoz Gama, Jorge, Carmona, J., van Dongen, Boudewijn & van der Aalst, Wil (2015). Measuring precision of modeled behavior. Information Systems and e-Business Management, 13(1), 37-67. Claes, Jan, Vanderfeesten, Irene, Pinggera, J., Reijers, Hajo, Weber, B. & Poels, G. (2015). A visual analysis of the process of process modeling. Read More …
