A 2-tuple fuzzy linguistic representation model for computing with words
Abstract
The fuzzy linguistic approach has been applied successfully to many problems. However, there is a limitation of this approach imposed by its information representation model and the computation methods used when fusion processes are performed on linguistic values. This limitation is the loss of information; this loss of information implies a lack of precision in the final results from the fusion of linguistic information. In this paper, we present tools for overcoming this limitation. The linguistic information is expressed by means of 2-tuples, which are composed of a linguistic term and a numeric value assessed in (-0.5, 0.5). This model allows a continuous representation of the linguistic information on its domain, therefore, it can represent any counting of information obtained in a aggregation process. We then develop a computational technique for computing with words without any loss of information. Finally, different classical aggregation operators are extended to deal with the 2-tuple linguistic model.
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The arithmetic mean method was chosen to aggregate experts' linguistic evaluations to prevent data loss.
“To prevent data loss, we choose the arithmetic mean method to aggregate the experts' linguistic evaluations [53].”
From Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making (2025) · cites this paper as [53]
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Naz, S., Butt, S. A., ul Hassan, M. M., Escorcia-Gutierrez, J., Fatima, A., & ul Ain, F. (2025) · Neurocomputing · doi:10.1016/j.neucom.2024.128615 · Cited by 17 · see citing works
Trustworthiness Evaluation of Large Language Models Using Multi-Criteria Decision Making
Aksoy, M., Adem, A., & Dağdeviren, M. (2025) · IEEE Access · doi:10.1109/access.2025.3612568 · Cited by 10 · see citing works
“To prevent data loss, we choose the arithmetic mean method to aggregate the experts’ linguistic evaluations [53].”
- Authors
- Martinez, L., & Herrera, F.
- Affiliations
- Universidad de Granada (ES)
- ORCID
- Herrera, F.
- Venue
- IEEE Transactions on Fuzzy Systems
- Published
- 2000
- Volume
- 8
- Issue
- 6
- Pages
- 746-752
- ISSN
- 1063-6706 (ISSN-L)
- OpenAlex
- W2117827905
- Cited by
- 2,662
- References
- 0
- Citations by year
- 2026: 62 · 2025: 93 · 2024: 144 · 2023: 194 · 2022: 184 · 2021: 178 · 2020: 147 · 2019: 198 · 2018: 185 · 2017: 165 · 2016: 123 · 2015: 151 · 2014: 169 · 2013: 121 · 2012: 98
- FWCI
- 12.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Fuzzy Systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Algebra and Logic
- Keywords
- 2-tuple linguistic representation model, computing with words, aggregation operators, information loss, linguistic terms
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