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基于深度神经网络的电力客户诉求预判
引用本文:彭路,朱君,邹云峰. 基于深度神经网络的电力客户诉求预判[J]. 计算机与现代化, 2020, 0(5): 22-28. DOI: 10.3969/j.issn.1006-2475.2020.05.004
作者姓名:彭路  朱君  邹云峰
作者单位:河海大学计算机与信息学院,江苏 南京 211100;国网江苏省电力有限公司营销服务中心,江苏 南京 210019
基金项目:国家重点研发计划;国网江苏省电力有限公司科技项目
摘    要: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,...

关 键 词:深度神经网络  客户诉求预判  电力客户服务工单  文本分类
收稿时间:2020-05-21

Prediction of Power Customer Demands Based on Deep Neural Network
PENG Lu,ZHU Jun,ZOU Yun-feng. Prediction of Power Customer Demands Based on Deep Neural Network[J]. Computer and Modernization, 2020, 0(5): 22-28. DOI: 10.3969/j.issn.1006-2475.2020.05.004
Authors:PENG Lu  ZHU Jun  ZOU Yun-feng
Abstract: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.
Keywords:deep neural network  customer demands forecast  power customer service order  text classification  
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