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Music recommendation using hypergraphs and group sparsity

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3 Author(s)
Theodoridis, A. ; Dept. of Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece ; Kotropoulos, C. ; Panagakis, Y.

A challenging problem in multimedia recommendation is to model a variety of relations, such as social, friend, listening, or tagging ones in a unified framework and to exploit all these sources of information. In this paper, music recommendation problem is expressed as a hypergraph ranking problem, introducing group sparsity constraints. By doing so, one can control how the different data groups (i.e., sets of hypergraph vertices) affect the recommendation process. Experiments on a dataset collected from demonstrate that the accuracy is significantly increased by exploiting the group structure of the data. Preliminary results are also presented for Greek folk music recommendation.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on

Date of Conference:

26-31 May 2013