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An Explainable Deep Ensemble Framework for Intelligent Ticket Management

Academic Article
Publication Date:
2023
abstract:
Pushing intelligence and integrating explainable tools in the new generation of ticket-management systems is cru-cial for supporting customer-support activities. To this aim, we defined a comprehensive ticket-classification frame-work, which integrates deep ensemble methods and AI -based interpretation techniques to help both the operator identify misclassification errors and the analyst improve the model. Tests on real data demonstrate the quality of the predictions returned by the framework and the practi-cal value of their associated explanations.
Iris type:
01.01 Articolo in rivista
Keywords:
Explainable AI
List of contributors:
Folino, Gianluigi; Pontieri, Luigi; Guarascio, Massimo
Authors of the University:
FOLINO GIANLUIGI
GUARASCIO MASSIMO
PONTIERI LUIGI
Handle:
https://iris.cnr.it/handle/20.500.14243/461928
Published in:
ERCIM NEWS
Journal
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URL

https://ercim-news.ercim.eu/images/stories/EN134/EN134-web.pdf
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