CityRec — A Data-Driven Conversational Destination Recommender System
Saadi Myftija, Linus W. Dietz · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 2020
In today's age of information, recommender systems have evolved to a must have feature for many platforms, especially in the area of travel and tourism. Destination recommender systems is a challenging domain, since unlike restaurants and points of interests, the items are not so well defined and no reliable rating information is available. Thus, we propose a data-driven characterization of cities, which is then directly used in a conversational recommender system. Through this, we overcome the costly elicitation of expert-based destination characterization, as well as the cold start problem of recommender systems. The recommender system can be used at http://cityrec.cm.in.tum.de/ and the source code has been published.