Modelo de recomendación de alojamientos turísticos mediante machine learning, con extracción de información a través de la técnica web scraping

Abstract

According to the World Tourism Organization (UNWTO), tourism is a social, cultural, and economic phenomenon involving the movement of people to countries or places outside their usual environment for personal, professional, or business purposes. These people are referred to as travelers and may be either tourists or excursionists, residents or non-residents, who visit destinations or engage in activities, some of which involve tourism expenditure (Lin et al., 2016). Accordingly, this research aims to develop a model capable of determining an algorithm that recommends accommodation to users based on a previous search conducted within a specific geographical area. Furthermore, one of the major challenges today is the acquisition of structured data (Krotov et al., 2020). Therefore, it is necessary to explore new methods of information acquisition, such as web scraping, which makes it possible to extract data from websites for subsequent analysis and processing (Iacus, 2015). These data can then be used to develop models, such as the recommendation model proposed in this research.