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
