Six Fuzzy Morphology Methods for Roles of Combines Standard Sentences Persian language
Year: 2024
Type: article
Abstract: Ability to remove ambiguities is one of the main characteristics of the fuzzy systems in resolving the problems like NLP and morphology. On the other hand, most of the conducted studies in the field of morphology of Farsi language are dealing with analysis of words by means of HMM statistical method. Therefore, this paper has conducted the statistical morphology in the role of words in a sentence in the two sets of independent roles like: “Subject, adverb, possess, possessive, subject, subject header, appositive, conjunct, conjunctive, exclamation and proclaimed” using Fuzzy system. Also, in this Fuzzy system, the Max (Product) Fuzzifier by Bi-gram labeling was used. In addition, regarding the importance of defuzzifier of step one, in all fuzzy systems, for the first time, 6 types of defuzzifiers of ‘Maximum membership, center of gravity, weighted average, mean of maximum, smallest of maximum, largest of maximum, center average’ were implemented and obtained results have shown that the Center of gravity defuzzifier method with the mean of 63.698% had better results in comparison with other defuzzifer methods.
Authors: Rezaei, Haniye, Motameni, Homayun, Barzegar, Behnam
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7085722648
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