Integration of Fuzzy and Deep Learning in Three-Way Decisions

Abstract

The problem of uncertainty is a challenging issue to solve in opinion mining models. Existing models that use machine learning algorithms are unable to identify uncertainty within online customer reviews because of broad uncertain boundaries. Many researchers have developed fuzzy models to solve this problem. However, the problem of large uncertain boundaries remains with fuzzy models. The common challenging issue is that there is a big uncertain boundary between positive and negative classes as user reviews (or opinions) include many uncertainties. Dealing with these uncertainties is problematic due in many frequently used words may be non-relevant. This paper proposes a three-way based framework which integrates fuzzy concepts and deep learning together to solve the problem of uncertainty. Many experiments were conducted using movie review and ebook review datasets. The experimental results show that the proposed three-way framework is useful for dealing with uncertainties in opinions and we were able to show that significant F-measure for two benchmark dataset.