基于深度神经网络的电力客户诉求预判

Prediction of Power Customer Demands Based on Deep Neural Network

电力企业的客户服务关系到客户的切身利益和企业的经营效益,提升客服系统对电力客户诉求预判的分析与理解能力是改善电力行业客服质量的重要途径之一。为高效、针对性地解决电力客户集中需求,做到“先于客户所想”,本文以深度神经网络技术为基础,针对电力领域改进传统的中文文本分词技术以及特征提取方法,给出电力客户诉求预判的方法和流程,并通过实验验证。本文提出的方法可快速精准地对电力客户服务工单文本进行分类,挖掘出隐藏的客户用电诉求,将服务由被动变主动,第一时间解决电力客户潜在诉求。

Customer service of electric power enterprises is related to the vital interests of customers and the business benefits of enterprises.Improving the analyzing and understanding ability of the customer service system for group customers’electricity consumption problems is one of the important ways to improve the quality of customer service for power industry.In order to solve the concentrated demand of power customers efficiently and pertinently,and achieve“before the customers think”,based on the deep neural network technology,this paper improves the traditional Chinese text segmentation technology and feature extraction method in the field of power,gives the method and flow of power customer demand pre-judgment,and verifies it through experiments.The proposed method can quickly and accurately classify the texts of power customer service order and excavate hidden customer power problems,which changes the service from passive to active and solves the potential demands of power customers at the first time.