Szalas, Andrzej Szalas, Alicja 2009 (English)In: Aspects of Natural Language Processing Essays Dedicated to Leonard Bolc on the Occasion of His 75th Birthday, Springer, 2009, 43-58Chapter in book (Refereed)
Fuzzy logics are one of the most frequent approaches to model uncertainty and vagueness. In the case of fuzzy modeling, degrees of belief and disbelief sum up to 1, which causes problems in modeling the lack of knowledge and inconsistency. Therefore, so called paraconsistent intuitionistic fuzzy sets have been introduced, where the degrees of belief and disbelief are not required to sum up to 1. The situation when this sum is smaller than 1 reflects the lack of knowledge and its value greater than 1 models inconsistency. In many applications there is a strong need to guide and interpret fuzzy-like reasoning using qualitative approaches. To achieve this goal in the presence of uncertainty, lack of knowledge and inconsistency, we provide a framework for qualitative interpretation of the results of fuzzy-like reasoning by labeling numbers with words, like true, false, inconsistent, unknown, reflecting truth values of a suitable, usually finitely valued logical formalism.
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5070
National CategoryEngineering and Technology
Identifiersurn:nbn:se:liu:diva-21992 (URN)10.1007/978-3-642-04735-0_2 (DOI)978-3-642-04734-3 (ISBN)oai:DiVA.org:liu-21992 (OAI)diva2:242262 (DiVA)