Exploring Task Execution Patterns in Event Graphs

Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Exploring Task Execution Patterns in Event Graphs. 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 Mining Read More …

Process tree discovery using a probabilistic inductive miner

Scheepens, R. J., Brons, D., & Fahland, D. (2022). Process tree discovery using a probabilistic inductive miner. (Patent No. US11500756B2). https://patents.google.com/patent/US20220075705A1/en Abstract Systems and methods for generating a process tree of a process are provided. An event log of the process is received. It is determined whether a base case applies to the event log Read More …

Process Mining over Multiple Behavioral Dimensions with Event Knowledge Graphs

Fahland, D. (2022). Process Mining over Multiple Behavioral Dimensions with Event Knowledge Graphs. In Process Mining Handbook (pp. 274-319). (Lecture Notes in Business Information Processing; Vol. 448). https://doi.org/10.1007/978-3-031-08848-3_9 Abstract Classical process mining relies on the notion of a unique case identifier, which is used to partition event data into independent sequences of events. In this Read More …

Multi-dimensional Process Analysis

Fahland, D. (2022). Multi-dimensional Process Analysis. In C. Di Ciccio, R. Dijkman, A. del Río Ortega, & S. Rinderle-Ma (Eds.), Business Process Management – 20th International Conference, BPM 2022, Proceedings: Lecture Notes in Computer Science (Vol. 13420, pp. 27-33). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Read More …

Discover Context-Rich Local Process Models (Extended Abstract)

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 …

Defining Meaningful Local Process Models

Brunings, M., Fahland, D., & van Dongen, B. (2022). Defining Meaningful Local Process Models. In M. Koutny, F. Kordon, & D. Moldt (Eds.), Transactions on Petri Nets and Other Models of Concurrency XVI (pp. 24-48). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13220 LNCS). Read More …

Signal Phrase Extraction: Gateway to Information Retrieval Improvement in Law Texts

Sidorova, N., & van der Veen, M. (2021). Signal Phrase Extraction: Gateway to Information Retrieval Improvement in Law Texts. In E. Schweighofer (Ed.), Legal Knowledge and Information Systems – JURIX 2021: The 34th Annual Conference (pp. 127-130). (Frontiers in Artificial Intelligence and Applications; Vol. 346). IOS Press. https://doi.org/10.3233/FAIA210327 Abstract NLP-based techniques can support in improving Read More …

Efficient Memory Utilization in Conformance Checking of Process Event Streams

Zaman, R., Hassani, M., & van Dongen, B. F. (2022). Efficient Memory Utilization in Conformance Checking of Process Event Streams. 437-440. https://doi.org/10.1145/3477314.3507217 Abstract Conformance checking (CC) techniques of the process mining field gauge the conformance of the events constituting a case with respect to a business process model. Online conformance checking (OCC) techniques assess such Read More …

Discovering Care Pathways for Multi-morbid Patients Using Event Graphs

Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2022). Discovering Care Pathways for Multi-morbid Patients Using Event Graphs. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers. (pp. 352-364). (Lecture Notes in Business Information Processing (LNBIP); 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. (2022). Privacy and Confidentiality in Process Mining: Threats and Research Challenges. ACM Transactions on Management Information Systems, 13(1), [11]. https://doi.org/10.1145/3468877 Abstract Privacy and confidentiality are very important prerequisites for applying process mining to Read More …

Quantifying the Re-identification Risk in Published Process Models

Maatouk, K., & Mannhardt, F. (2022). Quantifying the Re-identification Risk in Published Process Models. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers (Vol. 433, pp. 382-394). (Lecture Notes in Business Information Processing (LNBIP)). Springer. https://doi.org/10.1007/978-3-030-98581-3_28 Abstract Read More …

Responsible Process Mining

Mannhardt, F. (2022). Responsible Process Mining. In W. M. P. van der Aalst, & J. Carmona (Eds.), Process Mining Handbook (pp. 373-401). (Lecture Notes in Business Information Processing; Vol. 448). Springer. https://doi.org/10.1007/978-3-031-08848-3_12 Abstract The prospect of data misuse negatively affecting our life has lead to the concept of responsible data science. It advocates for responsibility Read More …

CPN IDE: An Extensible Replacement for CPN Tools That Uses Access/CPN

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 …

Narration as a Technique to Improve Process Model Comprehension: Tell Me What I Cannot See

Aysolmaz, B., Cayhani, F. N., & Reijers, H. A. (Accepted/In press). Narration as a Technique to Improve Process Model Comprehension: Tell Me What I Cannot See. In Proceedings of the 34th International Conference on Advanced Information Systems Engineering (CAiSE’22) Abstract Conceptual models play a vital role in the engineering of information systems. A variety of Read More …

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 …

Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions

Koorn, J. J., Lu, X., Mannhardt, F., Leopold, H., & Reijers, H. A. (2022). Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions. https://doi.org/10.24251/HICSS.2022.503 Abstract Process mining is a family of techniques that can aid healthcare organizations in improving their processes. Most existing process mining techniques do not provide insights Read More …

Animation as a dynamic visualization technique for improving process model comprehension

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 …

From Symbolic RPA to Intelligent RPA: Challenges for Developing and Operating Intelligent Software Robots

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 …

Conformance Checking: A Systemic View

Dongen, B. F. V. (2022). Conformance Checking: A Systemic View. In A. Marrella, & B. Weber (Eds.), Business Process Management Workshops – BPM 2021 International Workshops, Revised Selected Papers (pp. 61-72). (Lecture Notes in Business Information Processing; Vol. 436 LNBIP). https://doi.org/10.1007/978-3-030-94343-1_5 Abstract Within the field of process mining, conformance checking plays an important role. While Read More …

A Framework for Efficient Memory Utilization in Online Conformance Checking

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 …

Conformance checking of mixed-paradigm process models

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 …

Prefix Imputation of Orphan Events in Event Stream Processing

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 …

What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning

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 …

Actionable Conformance Checking: From Intuitions to Code

Carmona, J., Weidlich, M., & Dongen, B. V. (2020). Actionable Conformance Checking: From Intuitions to Code. In R-D. Kutsche, & E. Zimányi (Eds.), Big Data Management and Analytics – 9th European Summer School, eBISS 2019, Revised Selected Papers (pp. 1-24). (Lecture Notes in Business Information Processing; Vol. 390). Springer. https://doi.org/10.1007/978-3-030-61627-4_1 Abstract Conformance checking is receiving Read More …

Augmented Business Process Management Systems: A Research Manifesto

Dumas, M., Fournier, F., Limonad, L., Marrella, A., Montali, M., Rehse, J-R., Accorsi, R., Calvanese, D., Giacomo, G. D., Fahland, D., Gal, A., Rosa, M. L., Völzer, H., & Weber, I. (2022). Augmented Business Process Management Systems: A Research Manifesto. CoRR, abs/2201.12855. https://dblp.org/db/journals/corr/corr2201.html#abs-2201-12855

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 …

Multi-Dimensional Event Data in Graph Databases

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 …

Process Discovery Using Graph Neural Networks

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 …

Striking a new Balance in Accuracy and Simplicity with the Probabilistic Inductive Miner

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 …

Business Process Management – 18th International Conference, BPM 2020, Seville, Spain, September 13-18, 2020, Proceedings

Fahland, D., Ghidini, C., Becker, J., & Dumas, M. (Eds.) (2020). Business Process Management – 18th International Conference, BPM 2020, Seville, Spain, September 13-18, 2020, Proceedings. (Lecture Notes in Computer Science; Vol. 12168). Springer. https://doi.org/10.1007/978-3-030-58666-9

Business Process Management Forum – BPM Forum 2020, Seville, Spain, September 13-18, 2020, Proceedings

Fahland, D., Ghidini, C., Becker, J., & Dumas, M. (Eds.) (2020). Business Process Management Forum – BPM Forum 2020, Seville, Spain, September 13-18, 2020, Proceedings. (Lecture Notes in Business Information Processing; Vol. 392). Springer. https://doi.org/10.1007/978-3-030-58638-6

Information-preserving abstractions of event data in process mining

Leemans, S. J. J., & Fahland, D. (2020). Information-preserving abstractions of event data in process mining. Knowledge and Information Systems, 62(3), 1143–1197. https://doi.org/10.1007/s10115-019-01376-9 Abstract Process mining aims at obtaining information about processes by analysing their past executions in event logs, event streams, or databases. Discovering a process model from a finite amount of event data Read More …