Uncertain knowledge representation and reasoning with linguistic belief structures

In this paper, we extend the concept of Dempster-Shafer Belief Structures to the case of Linguistic Belief Structures, whose focal elements and probability mass assignments are linguistic, i.e. words modeled by Interval Type-2 Fuzzy Sets. We show that Linguistic Weighted Averages are pertinent tools...

Full description

Saved in:
Bibliographic Details
Published inInformation sciences Vol. 585; pp. 471 - 497
Main Authors Rajati, Mohammad Reza, Mendel, Jerry M.
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.03.2022
Subjects
Combination of evidence
Compatibility measures
Computing with words
Doubly normalized linguistic weighted averages
Interval type-2 fuzzy sets
Linguistic belief structures
Linguistic weighted averages
Lower probabilities
Upper probabilities
Linguistic belief structures
Interval type-2 fuzzy sets
Lower probabilities
Combination of evidence
Linguistic weighted averages
Upper probabilities
Compatibility measures
Doubly normalized linguistic weighted averages
Computing with words
Online AccessGet full text

Cover

More Information
Summary:In this paper, we extend the concept of Dempster-Shafer Belief Structures to the case of Linguistic Belief Structures, whose focal elements and probability mass assignments are linguistic, i.e. words modeled by Interval Type-2 Fuzzy Sets. We show that Linguistic Weighted Averages are pertinent tools for derivation of lower and upper probabilities from such Belief Structures, especially when words describing probability masses and focal elements are modeled by Interval Type-2 Fuzzy Sets synthesized by collecting data from subjects. We moreover introduce methods for performing operations on Linguistic Belief Structures as well as combining them. We demonstrate how Linguistic Belief Structures can be used to represent uncertainties in natural languages and present methods for inference from them.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2021.11.004