An Experiment on Transfer Learning for Suffix Prediction on Event Logs

van Luijken, M., Ketykó, I., & Mannhardt, F. (2024). An Experiment on Transfer Learning for Suffix Prediction on Event Logs. In J. De Weerdt, & L. Pufahl (Eds.), Business Process Management Workshops – BPM 2023 International Workshops, Utrecht, The Netherlands, September 11–15, 2023, Revised Selected Papers (pp. 31-43). (Lecture Notes in Business Information Processing; Vol. 492 LNBIP). Springer. Read More …

Building User Journey Games from Multi-party Event Logs

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 …

Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study

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 …

Event Granularity in User Journeys

Context This project is defined in the scope of the Smart Journey Mining project [1, 9]. The SJM project vision is to increase the quality of services by uniting research on customer journeys and process mining using new developments in logic-based analysis and artificial intelligence. Research in SJM is done together with SINTEF Digital (Norway), 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 …

Smart Journey Mining: Towards successful digitalisation of services

The digitalisation of our society’s service systems has fundamentally changed the way services are delivered to, and experienced by, humans. Although digital services are supposed to simplify our lives and increase our efficiency, they often frustrate and burden customers, users, and employees. The overall goal is to increase the quality of services and support the Read More …