Personal customized recommendation system reflecting purchase criteria and product reviews sentiment analysis - Wu Guanchen; Minkyu Kim; Hoekyung Jung (Institute of Advanced Engineering and Science, 2021)
As the size of the e-commerce market grows, the consequences of it are appearing throughout society. The business environment of a company changes from a product center to a user center and introduces a recommendation system. However, the existing research has shown a limitation in deriving customized recommendation information to reflect the detailed information that users consider when purchasing a product. Therefore, the proposed system reflects the user's subjective purchasing criteria in the recommendation algorithm. And conduct sentiment analysis of product review data. Finally, the final sentiment score is weighted according to the purchase criteria priority, recommends the results to the user.