Exploring Deep Neural Networks for Automated Ticket Classification

Manual categorization of service desk tickets may lead to dispatching of problem tickets to aninappropriateexpertgroup,delays the response time and interrupts the normal functioning of the business.Traditional machine learningapproachescan be applied to train an automated service desk ticket classif...

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Veröffentlicht in:NeuroQuantology 2022-01, Vol.20 (13), p.3922
Hauptverfasser: Paramesh, S P, SHREEDHARA, K S
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description Manual categorization of service desk tickets may lead to dispatching of problem tickets to aninappropriateexpertgroup,delays the response time and interrupts the normal functioning of the business.Traditional machine learningapproachescan be applied to train an automated service desk ticket classifier by mining the historical tickets.Sparsity, non-linearity, overfitting and handcrafting of features are some of the issues concerning the traditional ticket classifiers.This research work proposes a deep neural network model based on Convolution Neural Network (CNN) for the automated classification of service desk tickets.A real-world service desk ticket data is used to corroborate the efficiency of the proposed ticket classifier model and compared the results with the traditionalclassifiers.The proposed CNN model outperforms the chosen alternatives in terms of overall model performance.Benefits of the proposed model includes assignment of tickets to the correct domain groups,speedy resolution, improved productivity, uninterrupted business and customer satisfaction.
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subjects Algorithms
Artificial neural networks
Automation
Classification
Classifiers
Customer satisfaction
Datasets
Deep learning
Desks
End users
Literature reviews
Machine learning
Natural language
Neural networks
Semantics
Sparsity
Support vector machines
Text categorization
User interface
title Exploring Deep Neural Networks for Automated Ticket Classification
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