Sand Jensen, B. , Saez Gallego, J. and Larsen, J. (2012) A predictive model of music preference using pairwise comparisons. In: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 25-30 Mar 2012, pp. 1977-1980. ISBN 9781467300452 (doi: 10.1109/ICASSP.2012.6288294)
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Abstract
Music recommendation is an important aspect of many streaming services and multi-media systems, however, it is typically based on so-called collaborative filtering methods. In this paper we consider the recommendation task from a personal viewpoint and examine to which degree music preference can be elicited and predicted using simple and robust queries such as pairwise comparisons. We propose to model - and in turn predict - the pairwise music preference using a very flexible model based on Gaussian Process priors for which we describe the required inference. We further propose a specific covariance function and evaluate the predictive performance on a novel dataset. In a recommendation style setting we obtain a leave-one-out accuracy of 74% compared to 50% with random predictions, showing potential for further refinement and evaluation.
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Jensen, Dr Bjorn |
Authors: | Sand Jensen, B., Saez Gallego, J., and Larsen, J. |
College/School: | College of Science and Engineering > School of Computing Science |
ISSN: | 1520-6149 |
ISBN: | 9781467300452 |
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