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

Authors:
Hooman Tahayori;Alireza Sadeghian
Affiliations:
Department of Computer Science, Ryerson University, Toronto, ON, M5B 2K3, Canada;Department of Computer Science, Ryerson University, Toronto, ON, M5B 2K3, Canada
Venue:
International Journal of Advanced Intelligence Paradigms
Year:
2012

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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.