A framework for text classification using intuitionistic fuzzy sets

Abstract

Due to massively increasing of web pages and online documents, one of crucial processes to handle those documents is automatic (or at least semiautomatic) text classification. Based on the concept of intuitionistic fuzzy set (IFS), a framework for text classification is presented. In the framework, we introduce statistical methods to represent each document as an IFS and to learn a pattern of each document class. Then, a similarity measure for IFSs is applied in order to assign the most relevant class to a new document. The proposed framework with various similarity measures for IFSs is evaluated by benchmark datasets. The experimental results show that our framework yields satisfactory results.