Research on evaluation method of e-commerce platform customer relationship based on decision tree algorithm

Quan Zhang and Bohan Liu

International Journal of Information Technology and Management, 2024, vol. 23, issue 3/4, 291-303

Abstract: In order to overcome the problems of poor evaluation accuracy and long evaluation time in traditional customer relationship evaluation methods, this study proposes a new customer relationship evaluation method for e-commerce platform based on decision tree algorithm. Firstly, analyse the connotation and characteristics of customer relationship; secondly, the importance of customer relationship in e-commerce platform is determined by using decision tree algorithm by selecting and dividing attributes according to the information gain results. Finally, the decision tree algorithm is used to design the classifier, the weighted sampling method is used to obtain the training samples of the base classifier, and the multi-period excess income method is used to construct the customer relationship evaluation function to achieve customer relationship evaluation. The experimental results show that the accuracy of the customer relationship evaluation results of this method is 99.8%, and the evaluation time is only 51 minutes.

Keywords: decision tree algorithm; electronic commerce; customer relationship; multi-period excess income method; weighted sampling. (search for similar items in EconPapers)
Date: 2024
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