A Survey of Explainable E-Commerce Recommender Systems
Huaqi Gao, Shunke Zhou · 2022
Since the growing information overload has become more and more serious on the Web, especially in the field of e-commerce. The explainable recommender system plays a crucial role in providing users with explanations of recommendations to enhance customer satisfaction and loyalty. In recent years, various explainable recommender approaches have been proposed and applied in e-commerce. This survey will review the development of explainable recommender systems, existing methods to generate explainable recommendations, applications in the e-commerce field, and further discuss future directions that can be incorporated and implemented to improve the quality of explainable recommender systems.