Abstract
Conference Title: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Conference Start Date: 2017, July 9 Conference End Date: 2017, July 12 Conference Location: Naples, Italy A search process becomes an essential component of everyday routine for many users. Users constantly look for new, and more or less relevant items that they require for work or for entertainment. On multiple occasions, they try to find other users who match their ‘likes’ and ‘dislikes’. Many different methods and approaches have been proposed and developed to address such needs. The Pythagorean Fuzzy Sets have been proposed as a new class of non-standard fuzzy sets. They are related to the idea of Pythagorean membership grades (a, b) that satisfy the requirement a2 + b2 ≤ 1. The interesting aspect of those types of sets is their ability to express a positive support a — a positive membership grade, and a negative support b — a negative membership grade. In this paper, we propose a method based on the application of Pythagorean fuzzy relations for identifying a degree of matching between users based on their evaluations of items. We use triangular compositions to determine users that match positive evaluations, and users that agree on negative ones. The usage of Pythagorean fuzzy sets allows us to take into consideration both positive and negative aspects of evaluations and find users who like or dislike at least the same items as a given user likes or dislikes. The proposed approach is used to identify users that evaluate movies in a similar way.