This book examines one of the more common and wide-spread methodologies to deal with uncertainty in real-world decision making problems, the computing with word

Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitat

This book proposes a novel CWW model to personalize individual semantics in linguistic decision making, based on two new concepts: numerical scale and consisten

In this chapter, Herrera-Martınez 2-tuple linguistic representation model is extended for combining imprecise qualitative information using fusion rules drawn