A Bibliometric Analysis of Linguistic Variables Based on Intuitionistic Fuzzy Set

Rahim, N; Yusoff, B; Abdullah, L; Merigó, JM

A Bibliometric Analysis of Linguistic Variables Based on Intuitionistic Fuzzy Set

Rahim, N Yusoff, B Abdullah, L Merigó, JM

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Publisher:: BON VIEW PUBLISHING PTE
Publication Type:: Journal Article
Citation:: Journal of Computational and Cognitive Engineering, 2025, 4, (2), pp. 121-131
Issue Date:: 2025-05-23

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Field	Value	Language
dc.contributor.author	Rahim, N
dc.contributor.author	Yusoff, B
dc.contributor.author	Abdullah, L
dc.contributor.author	Merigó, JM
dc.date.accessioned	2026-02-02T03:24:05Z
dc.date.available	2026-02-02T03:24:05Z
dc.date.issued	2025-05-23
dc.identifier.citation	Journal of Computational and Cognitive Engineering, 2025, 4, (2), pp. 121-131
dc.identifier.issn	2810-9570
dc.identifier.issn	2810-9503
dc.identifier.uri	http://hdl.handle.net/10453/192673
dc.description.abstract	The intuitionistic fuzzy set (IFS) has been extensively investigated, particularly concerning linguistic variables. Therefore, several modifications of linguistic variables based on IFS have been proposed in the literature. This study aims to explore scientific data related to linguistic variables based on IFS through bibliometric analysis. Data were obtained from the Scopus database and analyzed using VOSviewer software to evaluate the structure, conceptual evolution, and trends. The Scopus database provided 329 documents spanning the years 2002–2024. Specifically, the study examines the distribution of published documents per year, the most frequent keywords, the most influential authors, and the most frequently referenced sources. By highlighting significant articles and outlining publication topics, this analysis helps to enhance the quality of reviews in this field. This bibliometric analysis provides valuable insights for researchers and practitioners interested in utilizing linguistic variables based on IFS, offering an overview of current research trends and suggesting potential directions for further study.
dc.language	en
dc.publisher	BON VIEW PUBLISHING PTE
dc.relation.ispartof	Journal of Computational and Cognitive Engineering
dc.relation.isbasedon	10.47852/bonviewJCCE52024574
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A Bibliometric Analysis of Linguistic Variables Based on Intuitionistic Fuzzy Set
dc.type	Journal Article
utslib.citation.volume	4
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2026-02-02T03:24:04Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	4
utslib.citation.issue	2

Abstract:

The intuitionistic fuzzy set (IFS) has been extensively investigated, particularly concerning linguistic variables. Therefore, several modifications of linguistic variables based on IFS have been proposed in the literature. This study aims to explore scientific data related to linguistic variables based on IFS through bibliometric analysis. Data were obtained from the Scopus database and analyzed using VOSviewer software to evaluate the structure, conceptual evolution, and trends. The Scopus database provided 329 documents spanning the years 2002–2024. Specifically, the study examines the distribution of published documents per year, the most frequent keywords, the most influential authors, and the most frequently referenced sources. By highlighting significant articles and outlining publication topics, this analysis helps to enhance the quality of reviews in this field. This bibliometric analysis provides valuable insights for researchers and practitioners interested in utilizing linguistic variables based on IFS, offering an overview of current research trends and suggesting potential directions for further study.

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http://hdl.handle.net/10453/192673