Machine learning project: understanding hospitality as a competitive differential in restaurant management

• Autor(a) principal: Oliveira, Paulo Sergio Gonçalves de
• Data de Publicação: 2020
• Outros Autores: Yoshiura, Thais Goldbard, Alves, Carlos Alberto
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Gestão e Projetos (GeP)
• Texto Completo: https://periodicos.uninove.br/gep/article/view/18748
• topic: Software Design; Naïve Bayes; Machine Learning; Hospitality in Service Competitiveness; Food and Beverage Management; Projeto de Software; Naïve Bayes; Machine Learning; Hospitalidade na Competitividade de Serviços; Gestão em Alimentos e Bebidas

The aim of this article is to present the development of a Machine Learning project to predict the classification of the customer in relation to the restaurant, thus enabling the use of Hospitality as a competitive differential. To achieve the objective, a Machine Learning project was developed, which involved the development of a script in the R language, which allows analysis and application in Restaurants, in order to support managers in decision-making and eventual actions to mitigate problems. In order to capture the experts' experience, a model was developed by applying the Naïve Bayes algorithm, which was trained using data obtained from the TripAdvisor Site, reaching a hit rate of around 84% with the test data. This value is acceptable for new analyzes with data from customer opinions, thus demonstrating that the project has achieved its objective.