期刊
EXPERT SYSTEMS
卷 36, 期 3, 页码 -出版社
WILEY
DOI: 10.1111/exsy.12375
关键词
contact centre; evolutionary algorithms; work quality evaluation
资金
- Italian regional grant Interventi per la ricerca applicata, sviluppo sperimentale e innovazione ' Active Contact System', Friuli Venezia Giulia''
- European Regional Development Fund (ERDF)
- CETA-CIEMAT
- Government of Spain
- project: A System for the Management and Analysis of (Spatio) Temporal Data,'' GAP Project 2014/15 of the University of Udine
In this work, a data set describing phone interactions arising in a multichannel and multiskill contact centre is considered with the aim of classifying inbound sessions into those that will be eventually managed by an agent and those that, instead, will be abandoned before. More precisely, the goal of the work is to extract interpretable pieces of information that allow us to predict whether a user will or will not abandon a call, which may turn out to be very useful for the purpose of contact centre managing. To this end, the performance of two well-known, state-of-the-art evolutionary algorithms for feature selection (evolutionary nondominated radial slots based algorithm and nondominated sorted genetic algorithm) is compared for the task of feature selection, under the criteria of accuracy and cardinality of the selection, as well as for the task of fuzzy rule extraction, under the criteria of interpretability, accuracy, and hypervolume test. The best obtained fuzzy classifier, chosen after a decision making process, is validated and interpreted by domain experts.
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