Getting cold start users connected in a recommender system's trust network

Generating personalized recommendations for new users is particularly challenging, because in this case, the recommender system has little or no user record of previously rated items. Connecting the newcomer to an underlying trust network among the users of the recommender system alleviates this so-called cold start problem. In this paper, we study the effect of guiding the new user through the connection process, and in particular the influence this has on the amount of generated recommendations. Experiments on a dataset from Epinions.com support the claim that it is more beneficial for a newcomer to connect to an identified key figure instead of to a random user.