Research on Association of 95598 Customer Service Work Orders Based on Sequential Frequent Pattern Mining. Issue 5 (June 2019)

• Record Type: Journal Article
• Authors: Xin, Xu; Jun, Fu; Zhijie, Sun; Li, Wang; Xiaowei, Liu.; Zhiguo, Li.
• Is Part Of: Journal of physics. Volume 1213:Issue 5(2019)
• Publication Date: 2019-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1213/5/052104
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the continuous development of social economy and people's living standard, people's demand for electricity is also increasing day by day, as well as the demand for power supply capability of power supply enterprises and service level of staff. This has brought greater pressure and challenges to power supply enterprises, and the most prominent challenge is how to deal with customer complaints. In order to reduce customer complaints, it is necessary to predict whether customers will complain in the future according to the call track of customers who have already reflected their demands. Therefore, in complaint prediction, frequent pattern mining based on customer call track is particularly important.