关键词: 客户流失, 数据挖掘, 信息融合, 人工蚁群算法

Abstract: Concerning the limitations of data mining methods in telecom customer churn prediction, a combination of information fusion and data mining technology is proposed by establishing customer churn prediction model on data level, feature level and decision-making level. Firstly, the customer churn predictors are determined. Secondly, customers are divided into groups with different features according to their differences in the feature space distribution. Lastly, customer churn prediction results of each group are obtained by weighted the predictions of different models which are established by using different methods, and the weight of each model is obtained through artificial ant colony algorithm. The experimental results show that the performance of customer churn prediction model based on information fusion is better than the traditional model.

Key words: customer churn, data mining, information fusion, artificial ant colony algorithm