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

Collaborative Filtering Ensemble for Personalized Name Recommendation