Abstract:
Binary classification is a critical process for opinion mining,
which classifies opinions or user reviews into positive or negative classes.
So far many popular binary classifiers have been used in opinion mining.
The problematic issue is that there is a significant uncertain boundary between positive and negative classes as user reviews (or opinions)
include many uncertainties. Many researchers have developed models to
solve this uncertainty problem. However, the problem of broad uncertain
boundaries still remains with these models. This paper proposes a threeway decision framework using semantic rules and fuzzy concepts together
to solve the problem of uncertainty in opinion mining. This framework
uses semantic rules in fuzzy concepts to enhance the existing three-way
decision framework proposed by authors. The experimental results show
that the proposed three-way framework effectively deals with uncertainties in opinions using relevant semantic rules.
