Designing Micro-intelligences for Situated Affective Computing

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

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

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

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

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

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.