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IEAAIE
2004
Springer

Data Mining Approach for Analyzing Call Center Performance

12 years 1 months ago
Data Mining Approach for Analyzing Call Center Performance
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classification and regression trees, support vector machines and finally a hybrid decision tree – neural network approach) to the problem of predicting the quality of service in call centers; based on the performance data actually collected in a call center of a large insurance company. Our aim was two-fold. First, to compare the performance of models built using the abovementioned techniques and, second, to analyze the characteristics of the input sensitivity in order to better understand the relationship between the performance evaluation process and the actual performance and in this way help improve the performance of call centers. In this paper we summarize our findings.
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where IEAAIE
Authors Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srinivas Mukkamala
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