• DocumentCode
    244661
  • Title

    An auxiliary recommendation system for repetitively purchasing items in E-commerce

  • Author

    Yoon Kyoung Choi ; Sung Kwon Kim

  • Author_Institution
    Smart Inf. Technol. Dept., Baewha Women´s Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    15-17 Jan. 2014
  • Firstpage
    96
  • Lastpage
    98
  • Abstract
    In the recommendation system suitable for products showing repetitive purchase pattern, we can use the repeat count of purchase for each product per user as a recommendation criteria. We implemented a system that recommends Products by user-based Collaborative Filtering and item-based Collaborative Filtering method, and recommends Associate Products analyzed by Association Rules.
  • Keywords
    collaborative filtering; data mining; electronic commerce; purchasing; recommender systems; E-commerce; associate products; association rules; auxiliary recommendation system; item-based collaborative filtering method; repetitive purchase pattern; repetitively purchasing items; user-based collaborative filtering; Algorithm design and analysis; Association rules; Collaboration; Educational institutions; Prediction algorithms; Recommender systems; Association Rules; Collaborative Filtering; E-Commerce; Recommendation System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data and Smart Computing (BIGCOMP), 2014 International Conference on
  • Conference_Location
    Bangkok
  • Type

    conf

  • DOI
    10.1109/BIGCOMP.2014.6741415
  • Filename
    6741415