Product Recommendation System based on User Purchase Priority

  • Bang, Jinsuk (Department of Computer Engineering, Hoseo University) ;
  • Hwang, Doyeun (Department of Computer Engineering, PaiChai University) ;
  • Jung, Hoekyung (Department of Computer Engineering, PaiChai University)
  • Received : 2019.12.03
  • Accepted : 2020.02.13
  • Published : 2020.03.31


As personalized customer services create a society that emphasizes the personality of an individual, the number of product reviews and quantity of user data generated by users on the internet in mobile shopping apps and sites are increasing. Such product review data are classified as unstructured data. Unstructured data have the potential to be transformed into information that companies and users can employ, using appropriate processing and analyses. However, existing systems do not reflect the detailed information they collect, such as user characteristics, purchase preference, or purchase priority while analyzing review data. Thus, it is challenging to provide customized recommendations for various users. Therefore, in this study, we have developed a product recommendation system that takes into account the user's priority, which they select, when searching for and purchasing a product. The recommendation system then displays the results to the user by processing and analyzing their preferences. Since the user's preference is considered, the user can obtain results that are more relevant.


Supported by : PaiChai University


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