  Recommender algorithms performance is often associated with the availability
of sufficient historical rating data. Unfortunately, when it comes to children,
this data is seldom available. In this paper, we report on an initial analysis
conducted to examine the degree to which data about traditional users, i.e.,
adults, can be leveraged to enhance the recommendation process for children.
