Article: A General Framework for Context-Aware Fuzzification of Four Ordered Categories: A Case Study on BMI Categories
Alternative Title
Authors
Alijani, Zahra
Daňková, Martina
Editor
Abstract
This 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.
Description
Subject Headings
fuzzy systémy, matematika, informatika
Keywords
fuzzy systems, mathematics, informatics
ISBN
ISSN
DOI
10.15452/978-80-7599-515-5.2026.02
License
CC BY 4.0
Citation
ALIJANI, 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.