A Fuzzy Linguistic IRS Model Based on a 2-Tuple Fuzzy Linguistic Approach

@article{HerreraViedma2007AFL,
  title={A Fuzzy Linguistic IRS Model Based on a 2-Tuple Fuzzy Linguistic Approach},
  author={Enrique Herrera-Viedma and Antonio Gabriel L{\'o}pez-Herrera and Mar{\'i}a Luque and Carlos Porcel},
  journal={International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  year={2007},
  volume={15},
  pages={225-250}
}
Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.