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Augmentation of Behavioral Analysis Framework for E-Commerce Customers Using MLP-Based ANN

  • Kailash HambardeEmail author
  • Gökhan Silahtaroğlu
  • Santosh Khamitkar
  • Parag Bhalchandra
  • Husen Shaikh
  • Pritam Tamsekar
  • Govind Kulkarni
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 37)

Abstract

The presented investigations deal with the implementation of data analytics over Turkey-based e-commerce company’s data repositories. The main objective is to hunt for classification of the customer’s behavior patterns. Artificial neural network (ANN) model was applied over customer’s dataset to forecast the customer’s purchasing patterns. The result would benefit the marketing department to recognize the targeted customers for specific campaigning activity. The efficiency of ANN models was also tested. The obtained results revealed that the neural network model using back-propagation technique has high accuracy toward customer prediction. The implementations were carried out in R programming environment.

Keywords

Data analytics Customer behavior analysis Classification MLP ANN 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Kailash Hambarde
    • 1
    Email author
  • Gökhan Silahtaroğlu
    • 2
  • Santosh Khamitkar
    • 1
  • Parag Bhalchandra
    • 1
  • Husen Shaikh
    • 1
  • Pritam Tamsekar
    • 1
  • Govind Kulkarni
    • 1
  1. 1.School of Computational SciencesSRTM University NandedNandedIndia
  2. 2.School of Business and Management ScienceI.M. UniversityIstanbulTurkey

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