Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2022). An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns. In W. Chen, L. Yao, T. Cai, S. Pan, T. Shen, & X. Li (Eds.), Advanced Data Mining and Applications – 18th International Conference, ADMA 2022, Proceedings (pp. 397-412). (Lecture Notes in Computer Read More …
Mehr, A. S. M., de Carvalho, R. M., & van Dongen, B. (2021). MLA: A Tool for Multi-Perspective Conformance Checking of Business Processes. In ICPM 2021 Doctoral Consortium and Demo Track 2021 (pp. 35-36). (CEUR Workshop Proceedings; Vol. 3098). CEUR-WS.org. https://ceur-ws.org/Vol-3098/demo_200.pdf Abstract Existing conformance checking techniques focus more on the control-flow perspective rather than other Read More …
Sommers, D., Sidorova, N., & van Dongen, B. (2022). Aligning Event Logs to Resource-Constrained ν-Petri Nets. In L. Bernardinello, & L. Petrucci (Eds.), Application and Theory of Petri Nets and Concurrency – 43rd International Conference, PETRI NETS 2022, Proceedings (pp. 325-345). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More …
Andersen, E., Chiarandini, M., Hassani, M., Janicke, S., Tampakis, P., & Zimek, A. (2022). Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection. In Proceedings – 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022 (pp. 64-69). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MDM55031.2022.00030 Abstract Recent approaches have proven the effectiveness Read More …
Spenrath, Y., Hassani, M., & Dongen, B. F. V. (2022). Clustering-based Aggregations for Prediction in Event Streams. CoRR, abs/2210.09738. https://doi.org/10.48550/arXiv.2210.09738
Klijn, E. L., Mannhardt, F., & Fahland, D. (2023). Aggregating Event Knowledge Graphs for Task Analysis. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 493-505). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_36 Abstract Aggregation of event data is a Read More …
Kobialka, P., Mannhardt, F., Tapia Tarifa, S. L., & Johnsen, E. B. (2023). Building User Journey Games from Multi-party Event Logs. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 71-83). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_6 Abstract To Read More …
Dubbeldam, A. L., Ketykó, I., de Carvalho, R. M., & Mannhardt, F. (2023). Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 366-377). (Lecture Notes in Business Information Processing; Read More …
Augusto, A., Carmona, J., & Verbeek, H. M. W. (2022). Advanced Process Discovery Techniques. In Process Mining Handbook (pp. 76-107). (Lecture Notes in Business Information Processing (LNBIP); Vol. 448). Springer. https://doi.org/10.1007/978-3-031-08848-3_3 Abstract Given the challenges associated to the process discovery task, more than a hundred research studies addressed the problem over the past two decades. Read More …
Verbeek, H. M. W. (2022). Discovering an S-Coverable WF-net using DiSCover. In A. Burattin, A. Polyvyanyy, & B. Weber (Eds.), Proceedings of the 2022 4th International Conference on Process Mining (ICPM 2022) (pp. 64-71). IEEE Press. https://doi.org/10.1109/ICPM57379.2022.9980723 Abstract Although many algorithms exist that can discover a WF-net from an event log, only a few (if Read More …
Spenrath, Y., Hassani, M., & van Dongen, B. F. (2022). Online Prediction of Aggregated Retailer Consumer Behaviour. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Revised Selected Papers (pp. 211-223). (Lecture Notes in Business Information Processing; Vol. 433 LNBIP). Springer. https://doi.org/10.1007/978-3-030-98581-3_16 Abstract Predicting the behaviour of consumers provides valuable Read More …
Spenrath, Y., Hassani, M., & Van Dongen, B. F. (2022). BitBooster: Effective Approximation of Distance Metrics via Binary Operations. In H. Va Leong, S. S. Sarvestani, Y. Teranishi, A. Cuzzocrea, H. Kashiwazaki, D. Towey, J-J. Yang, & H. Shahriar (Eds.), Proceedings – 2022 IEEE 46th Annual Computers, Software, and Applications Conference, COMPSAC 2022 (pp. 201-210). Read More …
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 …
Fahland, D., Ghidini, C., Dumas, M., & Reichert, M. (2022). Special issue: BPM 2020 Selected Papers in Foundations and Engineering. Information Systems, 109, [102093]. https://doi.org/10.1016/j.is.2022.102093
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 …
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 …
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 …
Fahland, D. (2022). Extracting and Pre-Processing Event Logs. CoRR, abs/2211.04338. https://doi.org/10.48550/arXiv.2211.04338
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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., 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 …
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 …
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 …
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 …
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 …
Hildebrandt, T., Dongen, B. F. V., Röglinger, M., & Mendling, J. (Guest ed.) (2022). Selected Papers of BPM 2019 – Editorial to the Special Issue. Information Systems, 104, [101902]. https://doi.org/10.1016/j.is.2021.101902
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 …
van Dongen, B. F., Montali, M., & Wynn, M. T. (Eds.) (2020). 2nd International Conference on Process Mining, ICPM 2020, Padua, Italy, October 4-9, 2020. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020
