Personalized travel suggestions for tourism websites

Abstract

The evolution of tourism websites is converging to a set of features and best practices that are becoming standard, in such a way that developing a template and later customizing it to a given tourist region is becoming feasible. A very important feature in this kind of site is showing the touristic suggestions of what the tourist can find in the destination, optimally personalized for him/her. One problem in deploying such functionality however is the lack of user experience data suited to perform data mining when a new site is launched. This paper proposes a solution, customizable to any touristic region, that harnesses the information available in Flickr, crossing it with a Point of Interest (POI) database and using Google Prediction API (Application Programming Interface) to generate personalized travel suggestions, based on the geographical itinerary the user defined with a trip planner tool.