Inteligência artificial para recomendação de roteiro de viagem personalizado

• Autor(a) principal: Ferreira, Gustavo Fernandes Ramos Júlio
• Data de Publicação: 2023
• Outros Autores: Chiesi Neto, Humberto, Silva, Julia Ferreira de Freitas, Calisto, Nicolas de Aguiar
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da PUC_SP
• Texto Completo: https://repositorio.pucsp.br/jspui/handle/handle/42580
• topic: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; Inteligência artificial; Roteiro turístico; K-Nearest Neighbour (KNN); Web scraping; Turista; Artificial intelligence; Tourist itinerary; K-Nearest Neighbour; Web scraping; Personalized; Tourist

In a scenario of travel shaped by individual experiences, the quest for personalized tourist itineraries is paramount. This study proposes an Artificial Intelligence (AI)-driven solution to provide itinerary recommendations aligned with each tourist's unique preferences, thereby incorporating the social context of every traveler. Effective interaction between the user and the system is pivotal, with the itinerary conceived as a set of attractions organized based on the tourist's choices and preferences. Each attraction is categorized, and detailed information is provided to substantiate the user's decision, offering a more meaningful immersion into their tourist journey. The implementation highlights the use of the k-Nearest Neighbour (KNN) algorithm to determine the attractions to be included in the itinerary. KNN analyzes the features of the initial attraction chosen by the tourist, ensuring precise recommendations, and avoiding disconnected experiences from their expectations, resulting in a more authentic immersion in the destination. It was possible to see an efficient solution to generate a various recommendation’s attractions, where they resemble in various ways