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English Information

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Authors
# Name
1 Felipe Bandeira da Silva(fbs@ecomp.poli.br)
2 Dimas Nascimento Filho(dimas.cassimiro@ufape.edu.br)
3 Bruno Nogueira(bruno@ic.ufal.br)

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Reference
# Reference
1 Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M. (2019). Optuna: A next-generation hyperparameter optimization framework. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), pages 2623–2631.
2 Alarifi, G., Rahman, M. F., and Hossain, M. S. (2023). Prediction and analysis of customer complaints using machine learning techniques. International Journal of E-Business Research, 19(1):1.
3 Almeida, R. J. A. (2018). LeIA – léxico para inferência adaptada. https://github.com/rafjaa/LeIA. Repositório GitHub.
4 An, Y., Yang, B., Hui, B., Zheng, B., Yu, B., Zhou, C., et al. (2024). Qwen2 technical report. arXiv preprint arXiv:2407.10671.
5 Baldo, F., Grando, J., Weege, K. M., and Bonassa, G. M. (2022). Adaptive fast XGBoost for binary classification. In Anais do XXXVII Simpósio Brasileiro de Banco de Dados (SBBD).
6 Blümel, J. and Zaki, M. (2022). Comparative analysis of classical and deep learning-based natural language processing for prioritizing customer complaints. In Proceedings of the 55th Hawaii International Conference on System Sciences, pages 1–10.
7 Carneiro, C. D., Duzert, Y., and Almeida, R. A. d. (2024). The economic benefits of business mediation in the Brazilian scenario. Revista de Administração de Empresas, 64(3):e2023–0145.
8 Gomes, L., Branco, A., Silva, J., Rodrigues, J., and Santos, R. (2024). Open sentence embeddings for Portuguese with the Serafim PT* encoders family. In Progress in Artificial Intelligence – 23rd EPIA Conference on Artificial Intelligence (EPIA 2024), pages 267–279, Cham. Springer Nature Switzerland.
9 Jondhale, R., Patil, S., Shinde, A., Ajalkar, D., and Biradar, S. (2024). Predicting consumer complaint disputes in finance using machine learning. In 2024 Second International Conference on Advances in Information Technology (ICAIT), pages 385–391.
10 Rabbi, G., Araújo, M., Kakizaki, G., Viterbo, J., Reis, J. C. S., Prates, R. O., and Gonçalves, M. A. (2024). Identificação e caracterização de reclamações duplicadas por consumidores em múltiplas plataformas. In Anais do XXXIX Simpósio Brasileiro de Banco de Dados (SBBD).
11 Santos, B. L., Ferreira, G. E., Ó, M. T. d., Braz, R. R., and Digiampietri, L. A. (2022). Comparison of natural language processing techniques in social bot detection on Twitter during Brazilian presidential elections. In Proceedings of iSys – Revista Brasileira de Sistemas de Informação.
12 Senacon (2024). Boletim consumidor.gov.br 2023. Boletim, Secretaria Nacional do Consumidor, Ministério da Justiça e Segurança Pública.
13 Silva, M. O., Oliveira, G. P., Costa, L. G. L., and Pappa, G. L. (2024). Evaluating domain-adapted language models for governmental text classification tasks in Portuguese. In Anais do XXXIX Simpósio Brasileiro de Banco de Dados (SBBD), page 247.
14 Sousa, G. N. d., Guimarães, I. d. S., Viana, J., Reinhold, O., Fernando, A., and Lobato, F. M. F. (2020). Análise do setor de telecomunicação brasileiro: Uma visão sobre reclamações. RISTI – Revista Ibérica de Sistemas e Tecnologias de Informação, 37:31–48.
15 Sujon, K. M., Hassan, R., Choi, K., and Samad, M. A. (2025). Accuracy, precision, recall, F1-score, or MCC? Empirical evidence from advanced statistics, ML, and XAI for evaluating business predictive models. Journal of Big Data, 12(1).
16 Vairetti, C., Aránguiz, I., Maldonado, S., Karmy, J. P., and Leal, A. (2023). Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making. European Journal of Operational Research, 312(3):1108–1122.
17 Vaishnav, D., Woo, J., et al. (2024). Predictive analysis of CFPB consumer complaints using machine learning. arXiv preprint arXiv:2407.06399.
18 Yang, Y., Xu, D., Yang, J., and Chen, Y. (2018). An evidential reasoning-based decision support system for handling customer complaints in mobile telecommunications. Knowledge-Based Systems, 162:202–214.