Clustering of Customers Based on Shopping Behavior and Employing Genetic Algorithms

Authors

  • E. P. Bafghi Department of Computer, Bafgh Branch, Islamic Azad University, Iran
Volume: 7 | Issue: 1 | Pages: 1420-1424 | February 2017 | https://doi.org/10.48084/etasr.752

Abstract

Clustering of customers is a vital case in marketing and customer relationship management. In traditional marketing, a market seller is categorized based on general characteristics like clients’ statistical information and their lifestyle features. However, this method seems unable to cope with today’s challenges. In this paper, we present a method for the classification of customers based on variables such as shopping cases and financial information related to the customers’ interactions. One measure of similarity was defined as clustering and clustering quality function was further defined. Genetic algorithms been used to ensure the accuracy of clustering.

Keywords:

classification, customers, shopping, genetic algorithm

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How to Cite

[1]
E. P. Bafghi, “Clustering of Customers Based on Shopping Behavior and Employing Genetic Algorithms”, Eng. Technol. Appl. Sci. Res., vol. 7, no. 1, pp. 1420–1424, Feb. 2017.

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