Softcomputing in neutrosophic linguistic modeling for the treatment of uncertainty in information retrieval

Abstract

Softcomputing is an extension of different concepts and techniques that try to overcome the difficulties presented by real problems that are imprecise, uncertain and difficult to categorize. The use of Softcomputing contributes to clarify that this term is not in itself a precise definition, but is a mixture of techniques, tools and methods that converge among themselves and each process has a specific objective. Within the group of Softcomputing techniques that are frequently used in linguistic modeling, for the treatment of uncertainty and the recovery of information, there is Neurocomputing, Probabilistic Reasoning, Fuzzy Logic and now neutrosophic Logic. In the present work, the combination of Softcomputing and neutrosophic logic is presented, for the neutrosophic linguistic modeling, in the treatment of uncertainty and information recovery, by means of a diffuse ordinal linguistic approximation. Modeling is performed by the linguistic information aggregation operator LOWA, which performs flexible modeling in the treatment of uncertainty and the evaluation of the proposed linguistic information retrieval. For this reason, the objective of this work is to deal with uncertainty in the process of recovering information.