Collaborative Filtering Ensemble

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M. Jahrer, A. Töscher ;
Proceedings of KDD Cup 2011, PMLR 18:61-74, 2012.

Abstract

This paper provides the solution of the team “commendo” on the Track1 dataset of the KDD Cup 2011 Dror et al.. Yahoo Labs provides a snapshot of their music-rating database as dataset for the competition. We get approximately 260 million ratings from 1 million users on 600k items. Timestamp and taxonomy information are added to the ratings. The goal of the competition was to predict unknown ratings on a testset with RMSE as error measure. Our final submission is a blend of different collaborative filtering algorithms. The algorithms are trained consecutively and they are blended together with a neural network.

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