van Delft, R. A. J. J., & de Carvalho, R. M. (2022). Using Machine Learning Techniques to Support the Emergency Department. Computing and Informatics, 41(1), 154-171. https://doi.org/10.31577/CAI_2022_1_154 Abstract This research lays down foundations for a stronger presence of machine learning in the emergency department. Using machine learning to make predictions on a patient’s situation can Read More …
Verdaasdonk, M. J. A., & de Carvalho, R. M. (2022). From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests. Healthcare Analytics, 2, Article 100040. https://doi.org/10.1016/j.health.2022.100040 Abstract One of the goals to improve the quality of care in hospitals is to set a maximum of four hours Read More …
Benzarti, I., Mili, H., Medeiros de Carvalho, R., & Leshob, A. (2022). Domain engineering for customer experience management. Innovations in Systems and Software Engineering, 18(1), 171-191. https://doi.org/10.1007/s11334-021-00426-2 Abstract Customer experience management (CXM) denotes a set of practices, processes, and tools, that aim at personalizing a customer’s interactions with a company around the customer’s needs and Read More …
de Carvalho, R. M., Nguyen, H., Heetveld, M., & Luime, J. (2022). An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence. In T. X. Bui (Ed.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 (pp. 4108-4117). IEEE Computer Society. Abstract The effects of Read More …
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 …
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
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 …
The course starts with an overview of the BPM domain using a set of twenty BPM use cases. These cover four key BPM activities: model (creating a process model to be used for analysis or enactment), enact (using a process model to control and support concrete cases), analyze (analyzing a process using a process model 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 …
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 …
Paul Kobialka, Felix Mannhardt, Silvia Lizeth Tapia Tarifa and Einar Broch Johnsen have won the Best Paper Award at the EdbA 2022 workshop for their paper titled “Building User Journey Games from Multi-party Event Logs”. Congratulations to Paul, Felix, Silvia and Einar!
Felix Mannhardt has won the Best Reviewer Award at ICPM 2022. Congratulations to Felix!
AlphaRevisitExperiments 6.12.20, by Aaron Küsters DiSCover 6.12.50, by Eric Verbeek ExogenousData 6.11.1, by Sander Leemans and Adam Banham ExtendedHybridMiner 6.12.9, by Humam Kourani and Chiara Di Francescomarini LongDistanceDependencies 6.12.19, by Sander Leemans LPMSupportedWords 6.12.4, by Mitchel Brunings StochasticLabelledPetriNets 6.12.44, by Sander Leemans, Fabrizio Maggi, and Marco Montali See also our ProM 6.12 development page.
Company Description Smart Host (https://www.smart-host.com) was founded in 2017 and is now one of the leading CRM systems for hotels in Europe. Based in Berlin, Germany we provide a SaaS solution to help hotels maximise their revenue and at the same time become better hosts by gathering valuable information about their guests and their individual 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 …
On September 14th, Bart Hompes and Marcus Dees won the “BPM Innovation award” with their submission “Detecting and mitigating the event log mutability problem at UWV (Uitvoeringsinstuut Werknemersverzekering)” to the Industry Forum at the BPM 2022 conference in Münster, Germany. Congratulations to Bart and Marcus!
The Winter School usually takes place in a weekend at the start of Q3. Details are announced 1 or 2 months in advance General course information Students are invited to join the Winter School by the EIT Digital co-location centre in the Netherlands
This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …
Only for BDMA students
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 …
In this meeting the student gets insight into the study program.
In this meeting the student gets insight into the study program.
Learning goals Students gain insight in basic techniques for processing large amounts of data in an efficient, reliable, and consistent way. Students develop skills in understanding, interpreting, and documenting data and information in the context of realistic scenarios. Students get understanding of the data life cycle and develop skills for structuring their solutions of practical Read More …
The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses. Data Challenge 3 is the final course in this series and shall familiarize students with the skills of designing and Read More …
