Linguistic Representation by Fuzzy Formal Concept and Interval Type-2 Feature Selection

Natural language is always seen as a source of uncertainty and vagueness. Fuzzy logic (FL) is a powerful tool for representing and treating perceptions which are the inputs and outputs of a linguistic model. In fact, a linguistic representation is a methodology that moves from crisp measures to uncertain words or fuzzy concepts. This theory uses fuzzy sets to encode and represent linguistic concepts. In this paper, an interval type-2 fuzzy formal concept IT-2FFC is presented as a new approach for extracting knowledge in a linguistic model. The method represents a combination of two techniques: fuzzy formal concept (FFC) for visualizing data and interval type-2 fuzzy sets (IT-2FSs) for feature selection. The obtained results demonstrate that the method applied can help human to make subjective judgments and make decision in a knowledge model.