Research Area: Recommender Systems in Tourism
Description of this research area
Recommender Systems (RSs) are information search and filtering tools that provide suggestions for items to be of use to a user. They have become common in a large number of Internet applications, helping users to make better choices while searching for news, music, vacations or financial investments. RSs exploit data mining and information retrieval techniques to predict to what extent an item suits the user needs and wants and recommend those items with the largest predicted fit score. Tourism applications have focussed on recommending: destinations, activities, accommodations and routes.
Prof. Dr. Francesco Ricci
Research projects in this research area
Publications published by this institute characterizing this research area
Braunhofer, M., Elahi, M., & Ricci, F. (2015). User Personality and the New User Problem in a Context-Aware Point of Interest Recommender System. In Information and Communication Technologies in Tourism 2015 (pp. 537-549). Springer International Publishing.
Ricci, F. (2010). Mobile recommender systems. Information Technology & Tourism, 12(3), 205-231.
Mahmood, T., Ricci, F., & Venturini, A. (2009). Improving recommendation effectiveness: Adapting a dialogue strategy in online travel planning. Information Technology & Tourism, 11(4), 285-302.