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 …
Aysolmaz, B., & Reijers, H. A. (2021). Animation as a dynamic visualization technique for improving process model comprehension. Information and Management, 58(5), [103478]. https://doi.org/10.1016/j.im.2021.103478 Abstract Process models are widely used for various system analysis and design activities, but it is challenging for stakeholders to understand these complex artifacts. In this work, we focus on the Read More …
Herm, L. V., Janiesch, C., Reijers, H. A., & Seubert, F. (2021). From Symbolic RPA to Intelligent RPA: Challenges for Developing and Operating Intelligent Software Robots. In A. Polyvyanyy, M. T. Wynn, A. Van Looy, & M. Reichert (Eds.), Business Process Management – 19th International Conference, BPM 2021, Proceedings (pp. 289-305). (Lecture Notes in Computer Read More …
Zaman, R., Hassani, M., & van Dongen, B. F. (2021). A Framework for Efficient Memory Utilization in Online Conformance Checking. arXiv.org. https://arxiv.org/pdf/2112.13640.pdf Abstract Conformance checking (CC) techniques of the process mining field gauge the conformance of the sequence of events in a case with respect to a business process model, which simply put is an Read More …
van Dongen, B. F., De Smedt, J., Di Ciccio, C., & Mendling, J. (2021). Conformance checking of mixed-paradigm process models. Information Systems, 102, [101685]. https://doi.org/10.1016/j.is.2020.101685 Abstract Mixed-paradigm process models integrate strengths of procedural and declarative representations like Petri nets and DECLARE. They are specifically interesting for process mining because they allow capturing complex behavior in Read More …
Zaman, R., Hassani, M., & van Dongen, B. F. (2021). Prefix Imputation of Orphan Events in Event Stream Processing. Frontiers in Big Data, 4, [705243]. https://doi.org/10.3389/fdata.2021.705243 Abstract In the context of process mining, event logs consist of process instances called cases. Conformance checking is a process mining task that inspects whether a log file is Read More …
Burattin, A., De Weerdt, J., van Dongen, B., Claes, J., & van der Aalst, W. (2021). Special issue on business process intelligence. Computing, 103, 1-2. https://doi.org/10.1007/s00607-020-00856-z
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 …
Fahland, D., Pufahl, L., & Koschmider, A. (2021). Automatische Prozessaufnahme mit Process-Discovery. In R. Laue, A. Koschmider, & D. Fahland (Eds.), Prozessmanagement und Process-Mining – Grundlagen (pp. 235-268) https://doi.org/10.1515/9783110500165-012
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 …
Esser, S., & Fahland, D. (2021). Multi-Dimensional Event Data in Graph Databases. Journal on Data Semantics, 10(1-2), 109–141. https://doi.org/10.1007/s13740-021-00122-1 Abstract Process event data is usually stored either in a sequential process event log or in a relational database. While the sequential, single-dimensional nature of event logs aids querying for (sub)sequences of events based on temporal Read More …
Sommers, D., Menkovski, V., & Fahland, D. (2021). Process Discovery Using Graph Neural Networks. In C. Di Ciccio, C. Di Francescomarino, & P. Soffer (Eds.), Proceedings – 2021 3rd International Conference on Process Mining, ICPM 2021 (pp. 40-47) https://doi.org/10.1109/ICPM53251.2021.9576849 Abstract Automatically discovering a process model from an event log is the prime problem in process Read More …
Fahland, D. (2021). Process-Mining: Prozessanalyse mit Ereignisdaten. In R. Laue, A. Koschmider, & D. Fahland (Eds.), Prozessmanagement und Process-Mining – Grundlagen (pp. 165-198). Walter de Gruyter GmbH. https://doi.org/10.1515/9783110500165-010
Laue, R., Koschmider, A., & Fahland, D. (Eds.) (2021). Prozessmanagement und Process-Mining – Grundlagen. (De Gruyter Studium). Walter de Gruyter GmbH. https://doi.org/10.1515/9783110500165
Brons, D., Scheepens, R., & Fahland, D. (2021). Striking a new Balance in Accuracy and Simplicity with the Probabilistic Inductive Miner. In C. Di Ciccio, C. Di Francescomarino, & P. Soffer (Eds.), Proceedings – 2021 3rd International Conference on Process Mining, ICPM 2021 (pp. 32-39) https://doi.org/10.1109/ICPM53251.2021.9576864 Abstract Numerous process discovery techniques exist for generating process Read More …
Mozafari Mehr, A., Medeiros de Carvalho, R., & van Dongen, B. F. (2021). Detecting Privacy, Data and Control-Flow Deviations in Business Processes. In S. Nurcan, & A. Korthaus (Eds.), Intelligent Information Systems – CAiSE Forum 2021, Proceedings (pp. 82-91). (Lecture Notes in Business Information Processing; Vol. 424 LNBIP). Springer. https://doi.org/10.1007/978-3-030-79108-7_10 Abstract Existing access control mechanisms Read More …
Lövei, P., Nazarchuk, I., Aslam, S., Yu, B., Megens, C. J. P. G., & Sidorova, N. (2021). Designing Micro-intelligences for Situated Affective Computing. In R-H. Liang, A. Chiumento, P. Pawełczak, & M. Funk (Eds.), CHIIOT 2021: Workshops on Computer Human Interaction in IoT Applications Abstract In this position paper we show how micro-intelligences can be Read More …
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 …
Yorick Spenrath has won the Best Presentation award at the SA4PM 2021 workshop for his paper title “Online Prediction of Aggregated Retailer Consumer Behaviour“. Congratulations to Yorick!
Dominique Sommers, Vlado Menkovski, and Dirk Fahland have won the Best Paper award at ICPM 2021 with their paper “Process Discovery using Graph Neural Networks“. Congratulations to Dominique, Vlado, and Dirk!
Summary In the context of the “Process Mining in Logistics” research project between Vanderlande Industries, we are offering multiple Master projects aimed at laying the foundations for a “Thinking Assistant” for large-scale material handling systems. Such a “Thinking Assistant” shall support engineers and operators in faster identifying problems and root-causes, predicting possible problems, and proposing Read More …
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 …
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 …
Dirk Fahland won the Test of Time award for the paper “Repairing Process Models to Reflect Reality” (co-authored by Wil van der Aalst, see also the journal version of this paper). Congratulations to Dirk!
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 …
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 …
On August 2nd, Erandi Miranda started working as a lecturer assistant in the PA group. A big welcome to Erandi!
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
On January 15th, Dominique Sommers started working as PhD student in the PA group. Dominique will work under the supervision of Boudewijn van Dongen. A big welcome to Dominique!
Data als brandstof voor kunstmatige intelligentie; TU/e start nieuwe masteropleiding EINDHOVEN – Zonder brandstof komt een auto niet vooruit. Hetzelfde principe gaat op voor kunstmatige intelligentie: zonder voldoende en goede data is daar niets intelligents aan. Een nieuwe master van de TU/e combineert daarom die twee disciplines. Bron: ED
Summary In the context of the “Process Mining in Logistics” research project between Vanderlande Industries and TU Eindhoven, we are offering multiple Master projects on process mining on event data of large-scale material handling systems. The fundamental challenges addressed are size and volume (logistics process data is significantly larger than business processes) and integration of Read More …
Summary In the context of the “Process Mining in Logistics” research project between Vanderlande Industries, we are offering multiple Master projects on process mining on event data of large-scale material handling systems. The fundamental challenges addressed are size (logistics processes are a factor 10-100 larger than business processes), reliable performance analysis and process prediction. We Read More …
