Recommendation System Based on Opinion Mining: A Survey

Rapid data expansion brought on by the emergence of the Web and e-commerce websites has led to the issue of information overload. Recommendation systems (RSs) have played a significant role in addressing this issue by using different algorithms to analyze user behavior and preferences and use this information to provide personalized recommendations. It's important to note that most RSs were based on customers' personal information, ratings, and other information. Recently, many researchers have used review texts and the rich information they might provide to enhance traditional RSs. These researchers vary in their approach, each one has its way of using review texts and determining user preferences. This paper provides a brief survey of the recent studies that have tended to the users' reviews in their work and examines how these reviews might be used to overcome some of the major problems facing standard RS algorithms.