Chapter – Process Analytics

Process Mining over Multiple Behavioral Dimensions with Event Knowledge Graphs

Posted onJanuary 27, 2023January 27, 2023AuthorEric VerbeekLeave a comment

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 …

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

Posted onDecember 1, 2022December 1, 2022AuthorEric VerbeekLeave a comment

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 …

Responsible Process Mining

Posted onOctober 7, 2022October 7, 2022AuthorEric VerbeekLeave a comment

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 …

Automatische Prozessaufnahme mit Process-Discovery

Posted onFebruary 28, 2022February 28, 2022AuthorEric VerbeekLeave a comment

Fahland, D., Pufahl, L., & Koschmider, A. (2021). Automatische Prozessaufnahme mit Process-Discovery. In R. Laue, A. Koschmider, & D. Fahland (Eds.), Prozessmanagement und Process-Mining – Grundlagen (pp. 235-268) https://doi.org/10.1515/9783110500165-012

Process-Mining: Prozessanalyse mit Ereignisdaten

Posted onFebruary 28, 2022February 28, 2022AuthorEric VerbeekLeave a comment

Fahland, D. (2021). Process-Mining: Prozessanalyse mit Ereignisdaten. In R. Laue, A. Koschmider, & D. Fahland (Eds.), Prozessmanagement und Process-Mining – Grundlagen (pp. 165-198). Walter de Gruyter GmbH. https://doi.org/10.1515/9783110500165-010

Designing Micro-intelligences for Situated Affective Computing

Posted onDecember 1, 2021AuthorEric VerbeekLeave a comment

Lövei, P., Nazarchuk, I., Aslam, S., Yu, B., Megens, C. J. P. G., & Sidorova, N. (2021). Designing Micro-intelligences for Situated Affective Computing. In R-H. Liang, A. Chiumento, P. Pawełczak, & M. Funk (Eds.), CHIIOT 2021: Workshops on Computer Human Interaction in IoT Applications Abstract In this position paper we show how micro-intelligences can be Read More …

Mining process model descriptions of daily life through event abstraction

Posted onFebruary 12, 2021AuthorEric VerbeekLeave a comment

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining process model descriptions of daily life through event abstraction. In S. Kapoor, R. Bhatia, & Y. Bi (Eds.), Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016 (pp. 83-104). (Studies in Computational Intelligence; Read More …

A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing

Posted onJanuary 18, 2021AuthorEric VerbeekLeave a comment

Petersen, S. A., Mannhardt, F., Oliveira, M., & Torvatn, H. (2018). A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing. In Y. Rezgui, H. Afsarmanesh, & L. M. Camarinha-Matos (Eds.), Collaborative Networks of Cognitive Systems – 19th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2018, Proceedings (pp. 85-97). (IFIP Advances in Information Read More …

Overview of efficient clustering methods for high-dimensional big data streams

Posted onFebruary 4, 2020AuthorEric VerbeekLeave a comment

Hassani, M. (2019). Overview of efficient clustering methods for high-dimensional big data streams. In O. Nasraoui, & C-E. Ben N’Cir (Eds.), Clustering Methods for Big Data Analytics (pp. 25-42). (Unsupervised and Semi-Supervised Learning). Cham: Springer. https://doi.org/10.1007/978-3-319-97864-2_2 Abstract The majority of clustering approaches focused on static data. However, a big variety of recent applications and research Read More …

Using process analytics to improve healthcare processes

Posted onFebruary 4, 2020AuthorEric VerbeekLeave a comment

Hompes, B., Dixit, P., & Buijs, J. (2019). Using process analytics to improve healthcare processes. In S. Consoli, D. Reforgiato Recupero, & M. Petković (Eds.), Data Science for Healthcare: Methodologies and Applications (pp. 305-325). Cham: Springer. https://doi.org/10.1007/978-3-030-05249-2_12 Abstract Healthcare processes are inherently complex as each patient is unique and medical staff deviate from protocols, often Read More …

RapidProM : mine your processes and not just your data

Posted onSeptember 19, 2018November 14, 2019AuthorEric VerbeekLeave a comment

van der Aalst, W.M.P., Bolt Iriondo, A.J. & van Zelst, S.J. (2018). RapidProM : mine your processes and not just your data. In R. Klinkenberg & M. Hofmann (Eds.), RapidMiner : Data Mining Use Cases and Business Analytics Applications Chapman & Hall/CRC Press.