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A Personalized Recommendation Model in E Commerce Based on TOPSIS Algorithm

Author

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  • Liang Wang

    (School of Economics and Management, Beijing Institute of Graphic Communication, Beijing, China & Institute of Information System, Beijing Jiaotong University, Haidian, Beijing, China)

  • Runtong Zhang

    (Institute of Information System, Beijing Jiaotong University, Haidian, Beijing, China)

  • Huan Ruan

    (School of Economics and Management, Beijing Institute of Graphic Communication, Beijing, China)

Abstract

From the perspective of performance and universality, this paper analyzed the characteristics of typical technologies for personalized recommendation system, and then made a basic architecture for the improved model. With the architecture, this paper introduced a personalized recommendation model in e-commerce system. The model is based on an n-tiers structure and the TOPSIS algorithm, first standardize the user evaluation indexes, and then determine the indexes weights according to user's needs, and finally calculate the personalized recommendation results. This model can be applied to a variety of e-commerce applications, especially for the e-commerce application with structured or semi-structured products such as digital books, journals and other publications.

Suggested Citation

  • Liang Wang & Runtong Zhang & Huan Ruan, 2014. "A Personalized Recommendation Model in E Commerce Based on TOPSIS Algorithm," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 12(2), pages 89-100, April.
    • Handle: RePEc:igg:jeco00:v:12:y:2014:i:2:p:89-100
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