Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/80663
Título: | Performance comparison of Machine Learning algorithms in classifying information technologies incident tickets |
Autor(es): | Oliveira, Domingos F. Nogueira, Afonso S. Brito, Miguel A. |
Palavras-chave: | text mining natural language processing machine learning |
Data: | 22-Jul-2022 |
Editora: | Multidisciplinary Digital Publishing Institute |
Revista: | AI |
Citação: | Oliveira, D.F.; Nogueira, A.S.; Brito, M.A. Performance Comparison of Machine Learning Algorithms in Classifying Information Technologies Incident Tickets. AI 2022, 3, 601-622. https://doi.org/10.3390/ai3030035 |
Resumo(s): | Technological problems related to everyday work elements are real, and IT professionals can solve them. However, when they encounter a problem, they must go to a platform where they can detail the category and textual description of the incident so that the support agent understands. However, not all employees are rigorous and accurate in describing an incident, and there is often a category that is totally out of line with the textual description of the ticket, making the deduction of the solution by the professional more time-consuming. In this project, a solution is proposed that aims to assign a category to new incident tickets through their classification, using Text Mining, PLN and ML techniques, to try to reduce human intervention in the classification of tickets as much as possible, reducing the time spent in their perception and resolution. The results were entirely satisfactory and allowed to us determine which are the best textual processing procedures to be carried out, subsequently achieving, in most of the classification models, an accuracy higher than 90%, making its implementation legitimate. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/80663 |
DOI: | 10.3390/ai3030035 |
e-ISSN: | 2673-2688 |
Versão da editora: | https://www.mdpi.com/2673-2688/3/3/35 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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ai-03-00035-v3.pdf | 1,05 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons