中文摘要：

针对当前客户分类变化挖掘方法的不足，提出了一种基于最佳分裂点的客户分类变化挖掘方法．根据分类规则的特点，调整了变化类型的定义，并在定义的基础上扩充了变化度量和变化程度测量的方法．为了不影响决策树中每个节点的最佳分裂点的寻找，在变化度量中提出了一个量化属性的属性值匹配度量方法．实证分析的结果表明，所提方法可以有效地识别2个不同时期的数据集的客户分类变化模式．

英文摘要：

Based on the best splitting point, a change mining methods of customer classification is proposed, which conquers the shortcomings of the existing change mining methods. In terms of the features of classification rule, the new definition of change types is proposed, based on which the metric of change and degree of change measures are redefined. In order not to affect the search for the best splitting point of each node in the decision tree, an extended measure of value match of quantitative attribute is designed to analyze the change measures between patterns. Empirical evaluation shows that the methodology is very effective to recognize the change of customer classification from two different datasets.