Predicting User Behaviour on E-Commerce Site Using Ann

  • Authors

    • Aditya Sai Srinivas
    • Somula Ramasubbareddy
    • Manivannan S.S
    • Govinda K
    2018-09-25
    https://doi.org/10.14419/ijet.v7i4.6.20454
  • Back Propagation, Layers, Machine Learning, SOM, Regression.

  • Abstract

    One of the major tasks for the modern business is learning to use all of the data available to them in a way that is both expressive and actionable. However, the potential for using data produced by a website is often left unfamiliar, and as a result, the objectives and feedbacks of individual digital customers can be unheeded. On the average website, there is a plenty of data to be collected about who interrelates with your site and how. By leveraging all of this statistics, we can gain perceptions into customer actions. Machine learning methods can be used to define which customers may be fascinated in achieving a result on your site.

     

     

     

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  • How to Cite

    Sai Srinivas, A., Ramasubbareddy, S., S.S, M., & K, G. (2018). Predicting User Behaviour on E-Commerce Site Using Ann. International Journal of Engineering & Technology, 7(4.6), 161-164. https://doi.org/10.14419/ijet.v7i4.6.20454

    Received date: 2018-09-29

    Accepted date: 2018-09-29

    Published date: 2018-09-25