• DocumentCode
    258382
  • Title

    Product recommendation system for small online retailers using association rules mining

  • Author

    Junnan Chen ; Miller, Colin ; Dagher, Gaby G.

  • fYear
    2014
  • fDate
    13-15 Aug. 2014
  • Firstpage
    71
  • Lastpage
    77
  • Abstract
    Recommendation systems in e-commerce have become essential tools to help businesses increase their sales. In this paper, we detail the design of a product recommendation system for small online retailers. Our system is specifically designed to address the needs of retailers with small data pools and limited processing power, and is tested for accuracy, efficiency, and scalability on real life data from a small online retailer.
  • Keywords
    Internet; data mining; electronic commerce; recommender systems; retailing; association rules mining; data pools; e-commerce; product recommendation system design; small online retailers; Algorithm design and analysis; Association rules; Companies; Databases; Libraries; Data Mining; Database Management; E-commerce; Performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Design and Manufacturing (ICIDM), Proceedings of the 2014 International Conference on
  • Conference_Location
    Montreal, QC
  • Print_ISBN
    978-1-4799-6269-3
  • Type

    conf

  • DOI
    10.1109/IDAM.2014.6912673
  • Filename
    6912673