Title: Median interval approach to model words with interval type-2 fuzzy sets

Authors: Hooman Tahayori; Alireza Sadeghian

Addresses: Department of Computer Science, Ryerson University, Toronto, ON, M5B 2K3, Canada ' Department of Computer Science, Ryerson University, Toronto, ON, M5B 2K3, Canada

Abstract: This paper introduces median interval approach (MIA) as a simple systematic method for modelling words from natural languages with interval type-2 fuzzy sets (IT2FS). The methodology is based on calculating the median boundaries of the range of membership functions associated with the words. MIA exhibits outlier tolerance which makes it applicable on different datasets gathered through various methods via different sources. Moreover, this approach provides consistent IT2FS models of words whereas they are generated based on different datasets. Experiments conducted on the datasets that are used in other researches show that the IT2FSs generated by MIA are more reasonable and better interpretable.

Keywords: interval type-2 fuzzy sets; IT2FS; computing with words; fuzzy logic; median interval; word modelling; natural language.

DOI: 10.1504/IJAIP.2012.052074

International Journal of Advanced Intelligence Paradigms, 2012 Vol.4 No.3/4, pp.313 - 336

Published online: 23 Aug 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article