FanOnTour: a novel approach to travel advisor systems

Current Travel advisor applications provide limited common features. There is a need to focus on new support functions for user satisfaction. Such systems must be designed to support surplus learning and users’ preferences and constraints. Different choices created in systems’ design can induce distinct decision strategies and influence the user’s affective state. The goal of this project is to develop a travel advisor system to assist users in their travel arrangements and decision-making. In this paper, we present a novel approach to take into account various factors to provide travel suggestions. These factors are user’s point of interest (POI), dislike list, distance, budget, transportation mode, the history of users and list of users’ friends. We demonstrate the validity of this approach using a case study and usability testing results.