Analysis Online Shopping Behavior of Consumer Using Decision Tree

被引：1

作者：

Yao, Leiyue ^{[1
]}

Xiong, Jianying ^{[1
]}

机构：

[1] Comp Sci Depatment, Hong Kong, Hong Kong, Peoples R China

来源：

ADVANCED MATERIALS AND INFORMATION TECHNOLOGY PROCESSING, PTS 1-3 | 2011年 / 271-273卷

关键词：

trading predict; decision tree; C5.0; TRUST;

D O I：

10.4028/www.scientific.net/AMR.271-273.891

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Trading failure is the main reason for a dispute of C2C e-commerce. So predict the behavior of transactions can assist buyers and sellers negotiated transactions, helps to reduce transaction disputes. Separate the success and failure purchase record, then establish decision-making model through the C5.0 decision tree and RFM(Recency, Frequency, Monetary) model on consumer purchase behavior data, quantify the importance of the decision variables, the demonstration experiment shows the prediction accuracy is more than 80%.

引用

页码：891 / +

页数：2

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