Abstract：A model structure on the analysis of customer behavior was constructed by using customer value feature and emotion feature for web customer churn prediction. The structure was used in web customer churn prediction for home electronic business carrier by comparing with support vector machine, artificial neural network, logistic regression, naive Bayesian classifier and decision tree. It is found that the structure has better accuracy with acceptable explanation of prediction model, and provides an effective approach for studying on two types of errors for web customer churn.
夏国恩，马文斌，唐婵娟，张显全. 融入客户价值特征和情感特征的网络客户流失预测研究[J]. 管理学报, 2018, 15(3): 442-.
XIA Guoen，MA Wenbing，TANG Chanjuan，ZHANG Xianquan. Study on the Value Feature and the Emotion Feature to Predict the Web Customer Churn. Chinese Journal of Management, 2018, 15(3): 442-.
