Abstract
This paper describes the application of a fuzzy version of Unsupervised Decision Tree (UDT) to the problem of an emergency call center. The goal is to obtain a decision support system that helps in the resource planning, reaching a trade-off between efficiency and quality of service. To reach this objective, the different types of days have been characterized based on variables that permits available resources assignment in an easy and understandable way. In order to deal with availability of expert knowledge on the problem, an unsupervised methodology had to be used, so fuzzy UDT is a solution merging decision trees and clustering, providing the performance of both viewpoints. Quality indexes give criteria for the selection of a reasonable solution to the complexity, as well as interpretability of the trees and the quality of generated clusters, and also the type of days and the performance from the resources point of view.
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Barrientos, F., Sainz, G. (2010). Knowledge Extraction Based on Fuzzy Unsupervised Decision Tree: Application to an Emergency Call Center. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13025-0_21
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DOI: https://doi.org/10.1007/978-3-642-13025-0_21
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