PT  - JOURNAL ARTICLE
AU  - Koukal, Filip
AU  - Dařena, František
AU  - Ježdík, Roman
AU  - Přichystal, Jan
TI  - Improving Automated Categorization of Customer Requests with Recent Advances in Natural Language Processing
DP  - 2024 Dec 31
TA  - European Journal of Business Science and Technology
PG  - 173--184
VI  - 10
IP  - 2
AID - 10.11118/ejobsat.2024.010
IS  - 23366494
AB  - In this paper, we focus on the categorization of tickets in service desk systems. We employ modern neural network-based artificial intelligence methods to improve the performance of current systems and address typical problems in the domain. Special attention is paid to balancing the ticket categories, selecting a suitable representation of text data, and choosing a classification model. Based on experiments with two real-world datasets, we conclude that text preprocessing, balancing the ticket categories, and using the representations of texts based on fine-tuned transformers are crucial for building successful classifiers in this domain. Although we could not directly compare our work to other research the results demonstrate superior performance to similar works.