CC BY 4.0Alijani, ZahraDaňková, Martina2026-02-062026-02-062026ALIJANI, Zahra and DAŇKOVÁ, Martina, 2026. A General Framework for Context-Aware Fuzzification of Four Ordered Categories: A Case Study on BMI Categories. Online. In: ; STUPŇANOVÁ, Andrea and PAVLISKA, Viktor (eds.). Proceedings of The Eighteenth International Conference on Fuzzy Set Theory and Applications. Ostrava: University of Ostrava, p. 25-28. ISBN 978-80-7599-515-5. Available at: https://doi.org/10.15452/978-80-7599-515-5.2026.02.10.15452/978-80-7599-515-5.2026.02https://eduo.osu.cz/handle/1/225This paper presents a general methodological framework for constructing context-aware fuzzy partitions that extend conventional crisp categorizations. The approach is based on Nov´ak’s theory of fuzzy contexts and is implemented using the R package lfl. It enables smooth and interpretable transitions between adjacent classes while preserving the original categorical structure. To illustrate the procedure, we apply it to derive fitness-specific fuzzy partitions of Body Mass Index, where the conventional four categories (underweight, normal weight, overweight, obese) are adapted according to individual levels of cardiorespiratory fitness.enfuzzy systemsmathematicsinformaticsinfo:eu-repo/semantics/conferencePaper519.1/.8 - Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelovánífuzzy systémymatematikainformatika