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NOS & Nova SBE Project-Based Learning - predicting the volume of customers to flag for call center’s specialized team : enhancing the performance of time series models through unsupervised outlier detection and treatment techniques

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Resumo:This thesis is part of a broader research effort extending the outcomes of the year-long Project-Based Learning initiative with NOS, a prominent telecommunications company in Portugal, focusing on optimizing the number of clients that should be flagged for specialized call center teams, to increase clients’ satisfaction. While the larger thesis addresses both model performance and explainability, this specific work focuses on improving model performance through outlier detection. By refining the handling of outliers, this study contributes to more accurate predictions, ultimately enhancing the effectiveness of client selection.
Autores principais:Muguerza, Victoria
Assunto:Call centers Time series forecasting Prediction modeling Unsupervised outlier detection Trimming Winsorization Robust estimation SARIMA XGBoost
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL

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