  Out of thousands of names to choose from, picking the right one for your
child is a daunting task. In this work, our objective is to help parents making
an informed decision while choosing a name for their baby. We follow a
recommender system approach and combine, in an ensemble, the individual
rankings produced by simple collaborative filtering algorithms in order to
produce a personalized list of names that meets the individual parents' taste.
Our experiments were conducted using real-world data collected from the query
logs of 'nameling' (nameling.net), an online portal for searching and exploring
names, which corresponds to the dataset released in the context of the ECML
PKDD Discover Challenge 2013. Our approach is intuitive, easy to implement, and
features fast training and prediction steps.
