Computing with Words Through Interval Type-2 Fuzzy Sets for Decision Making Environment

Abstract

Interval Type-2 fuzzy sets (IT2FSs) are used for modeling uncertainty and imprecision in a better way. In a conversation, the information given by humans are mostly words. IT2FSs can be used to provide a suitable mathematical representation of a word. The IT2FSs can be further processed using Computing with the words (CWW) engine to return the IT2FS output representation that can be decoded to give the output word. In this paper, an attempt has been made to develop a system that will help in decision making by considering person’s subjective importance for various factors for selection. For demonstration we have taken an example of restaurant recommender system that suggests the suitability of a restaurant depending on person’s subjective importance given to selection criteria (i.e.,cost, time and food quality). Firstly, a codebook is constructed to capture the vocabulary words. IT2FSs membership functions are used to represent these vocabulary words. The linguistic ratings corresponding to selection criteria are taken from experts for restaurants. The linguistic weights are person’s subjective importance given to the selection criteria. Finally, the CWW engine uses linguistic weights and linguistic ratings to obtain the suitability of the restaurant. The output is the recommended word which is also represented using IT2FS. The output word is more effective for human understanding in conversation where the precise information is not very useful and sometimes deceptive.