摘要
传统的网络购物只是对商品进行一个简单的分类和陈列,对于电子商务的商家并没有对网络消费者的购物数据进行深入研究探讨。针对网络购物过程中消费者选择商品的趋向性的不同,引入了基于决策树分类方法对网络客户购买商品的行为进行分析,并从决策树中挖掘出影响网络购物的主要因素以及各因素对网络购买行为的强弱影响程度。实验结果表明,此方法可以有效的对网络客户进行分类,有利于决策分析。
Traditional online shopping just a simple commodities classification and display,for e-commerce businesses and consumers shopping without depth study..Online shopping process for consumers to choose different tropism of goods,the introduction of decision tree classification method based on customers to buy goods on the network to analyze the behavior and dig out from the tree of the main factors affecting online shopping as well as various factors on the network impact strength of buying behavior.The experimental results show that this method can effectively classify clients on the network and favor decision analysis.
出处
《电子设计工程》
2014年第5期20-22,共3页
Electronic Design Engineering
关键词
决策树
网络客户分类
电子商务
数据挖掘
decision tree
classification
electronic commerce
data mining