Multi-model service for recommending tourist attractions

Abstract

Tourist information support is very important due to the fact that a tourist has to make decisions in dynamic and unfamiliar environment. One of the popular types of tourist decision support is recommendations (of attractions to see, events, transportation routes, etc.). However, each of the classical approaches for making recommendations relies heavily on the availability of particular information. This paper proposes a multi-model approach to recommendation systems design in the domain of tourist information support. Specifically, it proposes to construct a recommendation system as a composition of loosely coupled modules, implementing both personalized and non-personalized methods of recommendations and a coordination module responsible for adaptation of the whole system to the specific tourist and situation context. The paper also presents some results on practical evaluation of the proposed models and an integration of the developed recommendation system into a mobile tourist guide (TAIS).