Intelligent Research on Customer Complaints Based on 95598 Work Orders Track. Issue 2 (June 2019)

• Record Type: Journal Article
• Authors: Xin, Xu; Jun, Fu; Li, Wang; Dongmei, Gong; Yujun, Wang; Peilin, Tang
• Is Part Of: Journal of physics. Volume 1213:Issue 2(2019)
• Publication Date: 2019-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1213/2/022031
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the rapid development of society and economy, the living standard of people is continuously improving, which makes the society's demand for electricity increasing day by day, as well as the demand for power supply capability and service quality. When the power supply service enjoyed by customers does not meet the expected value, it will stimulate various demands of customers and even the customer complaints. How to accurately grasp customer demands and effectively prevent customer complaints is the key to improve customer satisfaction of power supply service and maintain a good image of power enterprises. The purpose of this article is to excavate the internal connection of the existing data through the serialization research based on the national power grid data, so as to predict whether users will make complaints after the call.