Methodological Approach for the Definition of Urban Tourist Patterns Through Data Mining

Electronic fare payment systems have gained much popularity around the world. These systems adopt a convenient and almost instantaneous payment process for public transport while also gathering data regarding onboard transactions in public transport. Much information about public transport passengers can be extracted, such as travel patterns, activities performed, and travel behavior. Despite the continuous growth of studies regarding these systems, there is still a lack of research to understand occasional passengers’ movement, such as tourists. This work presents the state of the art in these areas and presents a proposal to explore AFC data to understand the mobility profiles of tourists. This manuscript represents an advance in the literature and opens doors to the definition of policies to promote less visited places and mobility services adapted to tourists’ needs, resulting in a positive impact on the city’s economy and the overall enjoyment of the city for tourists.