Mô hình hệ thống khuyến nghị sản phẩm trong kinh doanh trực tuyến dựa vào khai thác dữ liệu phi cấu trúc - Lê Triệu , Tuấn; Phạm Minh, Hoàn (JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES, 2022)
Unstructured data generated by customers on e-commerce websites become an important matter in research and development of online recommendation system. It’s assisting for online customers in making purchasing decisions. These types of data are providing new research directions for solving the challenges of traditional recommendation systems. The study proposes a model of an online recommendation system based on exploiting customers’ comments. The system consists of two phases, the first is the unstructured data mining process and the second phase implements product recommendations according to the collaborative filtering model approach. Comment classification results integrated with the recommendation module to enhance information to users before they are making product selection decisions and overcome the problem of the new users. Therefore, the study proposes a way to build a virtual rating from the sentiment classification score instead of the real rating to overcome the problem of sparse data.