An Extension of Fuzzy Linguistic Summarization Considering Probabilistic Uncertainty

Abstract

Linguistic summarization provides to express large volumes of quantitative data in easy understandable natural language based forms. While various methods have been recommended for linguistic summarization, there is not any approach for linguistic summarization where possibilistic and probabilistic uncertainties exist together in data. In this study, we establish a tie between Z-number concept and type-I and type-II quantified sentences in order to calculate the truth degree of a linguistic summary covering possibilistic and probabilistic information. The proposed approach employs copulas to obtain a joint probability distribution of the variables included in type-II quantified sentence.