Exploiting item dependencies to improve tourist trip recommendations

Combining multiple points of interest (POIs) to attractive and reasonable tourist trips is a challenge in the field of Recommender Systems (RSs). Even if a user likes going to restaurants, a trip composed of too many restaurants will not be appreciated. In this position paper, we present our ideas how to improve tourist trip recommendations by focusing more on user satisfaction. We introduce the concept of item dependencies describing how POIs influence the value of other POIs in the same trip when recommending tourist trips. Besides background information and related work in the field of tourist trip recommendations, we present ideas to iteratively learn dependencies between items and to integrate them into the recommendation process.