Predicting Call Center Service Grade with Improved Neural Network Algorithm

Author

Lv Jing ; Guo Min

Author_Institution

Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China

fYear

2010

fDate

22-23 May 2010

Firstpage

1

Lastpage

4

Abstract

Call center has been paid more and more attention, a method for predicting call center service grade with improved neural network algorithm was put forward according to the call center service quality management requirements in the enterprise. The optimization algorithm Levenberg-Marquardt was utilized to increase the convergence speed of BP neural network. And overcome the shortcomings of falling into local minimum value easily. The data mining of call center system was realized offering a scientific and rational basis for the decision analysis to improve the level of call center services.

Keywords

backpropagation; customer services; data mining; decision making; neural nets; optimisation; outsourcing; quality management; BP neural network; Levenberg-Marquardt optimization algorithm; call center service grade prediction; data mining; decision analysis; improved neural network algorithm; quality management; Control engineering; Data mining; Data warehouses; Fault detection; Function approximation; Neural networks; Neurons; Predictive models; Statistical analysis; Telephony;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5872-1

Electronic_ISBN

978-1-4244-5874-5

Type

conf

DOI

10.1109/IWISA.2010.5473738

Filename

5473738