Design and Implementation of a Recommender System for Tourist Visit Management

Recommender systems are currently applied in many fields. They try to provide users with recommendation services based on their personalized preferences to reduce the ever increasing amount of information online. With the number of mobile phone users growing exponentially, travel guides have become an increasingly important search tool in recent years. Of course, we are not and will not be the first to implement a prototype to offer recommendations to users (tourists). Our particularity and/or novelty in this paper is to present a recommendation system to capture the optimal route taking into account both cost and distance constraints. The open dataset used covers information on tourist trip reviews of thousands of tourists who have visited different attractions in Italy and around the world. An association rule based on the exploratory approach will take into account the contextual information of the user's actual location to produce a dataset to be followed. In addition, a case study on tourism, Tourist visits, is implemented to verify the feasibility and applicability of the proposed system. The results of this work indicate that the proposed system has great potential to prepare the planning of tourists based on the use of mobile phones.