Background Customer journey thinking is getting more and more established in companies. Customers are getting more volatile with higher expectations and competition is fierce. With customer journey analytics it is possible to use a personal approach on a large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known Read More …
You’ve learned about process mining during your courses, but how much do you know about creating the event log for process mining? In business, creating the event log required for process mining is one of the most time-intensive, most complex parts of a process mining project. At Konekti, we’ve built a platform that simplifies and Read More …
On October 9th, Allmin Susaiyah started working as PostDoc in the PA group. Allmin will work under the supervision of Natalia Sidorova on the TACTICS project.
Process models are used to describe and reason about the execution of a process (e.g., package delivery) where a process instance (package), also called as a case, moves through the system. A case in a process is often subject to interaction with other cases and/or resources (e.g. deliverer), impacting the workflow. Event logs record which Read More …
Philips Healthcare produces an image-guided therapy system, called Azurion, that helps surgeons to execute complex procedures. In the past Master projects at Philips Healthcare, Master students have already developed a visual logfile analysis tool that has been making waves within our organization and conformance checking methods to address anti-patterns describing unwanted behavior. Now, we’re looking Read More …
Bakullari, B., Thoor, J. V., Fahland, D., & Aalst, W. M. P. v. d. (2023). The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them. In BPM (Forum) (pp. 145-162) https://doi.org/10.1007/978-3-031-41623-1_9
Sommers, D., Menkovski, V., & Fahland, D. (2023). Supervised learning of process discovery techniques using graph neural networks. Information Systems, 115, Article 102209. https://doi.org/10.1016/j.is.2023.102209 Abstract Automatically discovering a process model from an event log is the prime problem in process mining. This task is so far approached as an unsupervised learning problem through graph synthesis Read More …
Coremans, B., Klomp, A., Rukmono, S. A., Krüger, J., Fahland, D., & Chaudron, M. R. V. (2023). Process Mining from Jira Issues at a Large Company. In International Conference on Software Maintenance and Evolution (ICSME) IEEE Press.
Swevels, A., Dijkman, R. M., & Fahland, D. (2023). Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Proceedings (pp. 180-197). (Lecture Notes in Computer Science (LNCS); Vol. Read More …
Jessen, U., Sroka, M., & Fahland, D. (2023). Chit-Chat or Deep Talk: Prompt Engineering for Process Mining. CoRR, abs/2307.09909. https://doi.org/10.48550/arXiv.2307.09909
Dumas, M., Fournier, F., Limonad, L., Marrella, A., Montali, M., Rehse, J. R., Accorsi, R., Calvanese, D., De Giacomo, G., Fahland, D., Gal, A., La Rosa, M., Völzer, H., & Weber, I. (2023). AI-augmented Business Process Management Systems: A Research Manifesto. ACM Transactions on Management Information Systems, 14(1), Article 11. https://doi.org/10.1145/3576047 Abstract AI-augmented Business Process Read More …
Andreas Meyer, Luise Pufahl, Dirk Fahland and Mathias Weske have received the BPM Runner-Up Test-of-Time Award at BPM 2023 for their paper titled “Modeling and Enacting Complex Data Dependencies in Business Processes“.
Massimiliano de Leoni, Wil van der Aalst, and Marcus Dees have received the BPM Test-of-Time Award at BPM 2023 for their paper titled “A General Framework for Correlating Business Process Characteristics“.
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 …
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 …
In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics 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.
This course can only be followed by permission of the responsible lecturer. People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be organized in an ad-hoc manner taking into account the interests of the student. The focus will always be on a Read More …
In this meeting the student gets insight into the BDMA study program.
Many real-life phenomena studied with Data Science methods unfold over time. They often involve many people, objects, agents, machines, entities, etc. that interact with each other while distributed in time and space. Such dynamics are called processes and are present everywhere: in software systems medical treatments, logistics systems, manufacturing, and even entire organizations. Process mining Read More …
On September 1st, Freek van den Berg started working as PostDoc in the PA group. Freek will work under the supervision of Dirk Fahland on the AUTO-TWIN project. A big welcome to Freek!
Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2023). Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 44-56). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Read More …
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 …
Description Reliable analysis of performance problems and their root causes requires data of a high quality to understand how cases were handed from one employee to another and how they were processed in queues. However, the recorded event data is often of lower quality, e.g., information about queues is missing. The objective of this project Read More …
On January 1st, Ava Swevels started working as PhD student in the PA group. Ava will work under the supervision of Dirk Fahland on the AUTO-TWIN project. A big welcome to Ava!
