Earticle

초록

영어

Intelligent call center is also known as the customer service center or telephone service center, it is a kind of integrated information service system. This paper analyzes the classification method based on cost sensitive variable precision rough set. And in this paper, we use the attribute weighted cost sensitive rough set classification method based on established and customer level, customer history records, agents business related dynamic queuing strategy. In addition, this paper improves the multi fractal BP neural network algorithm for the call center customer classification. Improved algorithm is able to use multifractal fluctuation and BP neural network to predict the call center traffic and seat allocation. The paper presents construction of intelligent call center system based on cost sensitive variable precision rough set and multi fractal BP neural network. Experimental results show that novel method proposed can classify customers, reduce the impact of missing data and noise data, and improve the efficiency of customer satisfaction and intelligent call.

목차

Abstract
 1. Introduction
 2. Research on Decision Rough Set Analysis Based on Cost Sensitive
 3. The Combination of BP Neural Network and Multi Fractal Theory
 4. Design of Intelligent Call Center System Based on Cost Sensitive Variable Precision Rough Set and Multi Fractal BP Neural Network
 5. Experiments and Analysis
 6. Summary
 References

키워드

저자

• Hongsheng Xu [ Luoyang Normal University, Henan Luo Yang, China ]
• Ruiling Zhang [ Luoyang Normal University, Henan Luo Yang, China / School of Computer Science and Technology, Wuhan University of Technology, Hubei Wuhan, China ] Corresponding author
• Chunjie Lin [ Luoyang Normal University, Henan Luo Yang, China ]
• Youzhong Ma [ Luoyang Normal University, Henan Luo Yang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605