电力95598客户服务质检抽样算法研究

Research on Quality Inspection Sampling Algorithm of Electric 95598 Customer Service

为解决目前电力95598客服中心质检部门的质检抽样策略效率低、漏检率高等问题,提出利用改进的C4.5算法对客服话务和工单质量进行是否存在问题进行分类的质检抽样算法。该算法针对客服分类问题的非平衡性特点,将成本矩阵引入到C4.5算法中,利用Adaboost算法构建组合分类器来提升分类算法的准确性。在质检前利用质检抽样算法对所有客服话务和工单可能为问题话务或问题工单的概率进行预测,抽取有问题概率较大的客服话务和工单进行人工质检。实验结果表明,利用该质检抽样算法,可以将问题话务和工单的分类准确率从C4.5算法的66.67%提高到现在的78.49%,从而提高了被抽取的客服话务和工单中问题话务和问题工单的占比,证明该质检抽样算法是可行且有效的,能够提高质检效率、降低漏检率。

In allusion to defects such as low efficiency and high omission rate of sampling strategy in quality inspection department of electric 95598 Customer Service Center, a quality inspection sampling algorithm using modified C4.5 algorithm is proposed to classify service calls and work sheets with or without defects. Considering non-equilibrium character of service classification problem, the proposed algorithm introducing cost matrix to C4.5 algorithm and Adaboost algorithm is used to construct combined classifier to improve accuracy of classification algorithm. The proposed algorithm is used to predict incorrectness probability for each service call and work sheet, and only service calls and work sheets of high incorrectness probability are manually inspected. Experiments results show that classified accuracy of incorrect calls and work sheets is increased from 66.67% with C4.5 algorithm to 78.49% with quality inspection sampling algorithm, thus increasing ratio of incorrect service calls and work sheets in all samples. The proposed quality inspection sampling algorithm is feasible and valid, improving efficiency of quality inspection and reducing omission rate.