Service Recommendation System for a Smart City
Smart Cities are complex spaces with a variety of information and points of interest, in which citizens can have access, whether visitors or residents. This paper presents a system of recommendation of points of interest in smart cities, aiming to improve the result of the search performed by the user. For this, an ontological model was used, through a case study, adding data from a city. Through this study, it is possible to demonstrate the potential of an ontological modeling to provide recommendations. These improve semantics and create standardization to facilitate knowledge sharing. The approach developed aims to recommend information from sights and health services. To test the system, SWRL rules were developed and, from them, inferences are made by a reasoner.