Please use this identifier to cite or link to this item:
http://repositorio.inesctec.pt/handle/123456789/3618
Title: | On predicting a call center's workload: A discretization-based approach |
Authors: | Luís Moreira Matias Nunes,R Michel Ferreira João Mendes Moreira João Gama |
Issue Date: | 2014 |
Abstract: | Agent scheduling in call centers is a major management problem as the optimal ratio between service quality and costs is hardly achieved. In the literature, regression and time series analysis methods have been used to address this problem by predicting the future arrival counts. In this paper, we propose to discretize these target variables into finite intervals. By reducing its domain length, the goal is to accurately mine the demand peaks as these are the main cause for abandoned calls. This was done by employing multi-class classification. This approach was tested on a real-world dataset acquired through a taxi dispatching call center. The results demonstrate that this framework can accurately reduce the number of abandoned calls, while maintaining a reasonable staff-based cost. © 2014 Springer International Publishing. |
URI: | http://repositorio.inesctec.pt/handle/123456789/3618 http://dx.doi.org/10.1007/978-3-319-08326-1_59 |
metadata.dc.type: | conferenceObject Publication |
Appears in Collections: | CRACS - Articles in International Conferences LIAAD - Articles in International Conferences |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
P-009-NM6.pdf | 273.8 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.