Representation models for aggregating linguistic information: issues and analysis

The linguistic information has been used successfully in many areas. The aggregation of linguistic information is a crucial aspect. In the literature we can find different linguistic computational models that present linguistic aggregation operators as: (i) The computational model based on the Extension Principle, which operates over the fuzzy numbers that supports the semantics of the linguistic labels. (ii) The symbolic one makes the computations directly over the order index of the linguistic labels. And, (iii) the model based on the linguistic 2-tuple representation, which uses the symbolic translation to make the linguistic computations.Depending upon the linguistic aggregation model, different results can be obtained. In this chapter we shall make a comparative analysis of the aggregation approaches according to the results obtained in a decision-making application.

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