Novel linguistic relational Fuzzy Clustering

Abstract

The problem of clustering data is not only in the form of numeric values but also in the form of linguistic values e.g. very tall, not tall which is a type of uncertainty data. This thesis only focuses on represented as a pairwise relation between them which is called relational data. This research proposes linguistic relational fuzzy clustering to assess the effectiveness of the proposed method by experimenting with it on standard datasets and including a dataset from a recommendation system. From the results, our linguistic relational fuzzy clustering can cluster from fuzzy number and linguistic relational fuzzy clustering gives better results than relational fuzzy clustering.