This paper presents Myusic, a platform that leverages socialmedia to produce content-based music recommendations. The design ofthe platform is based on the insight that user preferences in music canbe extracted by mining Facebook profiles, thus providing a novel and ef-fective way to sift in large music databases and overcome the cold-startproblem as well. The content-based recommendation model implementedin Myusic is eVSM [4], an enhanced version of the vector space modelbased on distributional models, Random Indexing and Quantum Nega-tion. The effectiveness of the platform is evaluated through a preliminaryuser study performed on a sample of 50 persons. The results showed that74% of users actually prefer recommendations computed by social media-based profiles with respect to those computed by a simple heuristic basedon the popularity of artists, and confirmed the usefulness of performinguser studies because of the different outcomes they can provide withrespect to offline experiments.

Myusic: a Content-based Music Recommender System based on eVSM and Social Media / Musto, Cataldo; Narducci, Fedelucio; Semeraro, Giovanni; Lops, Pasquale; de Gemmis, Marco. - ELETTRONICO. - 964:(2013), pp. 65-72. (Intervento presentato al convegno 4th Italian Information Retrieval Workshop, IIR 2013 tenutosi a Pisa, Italy nel January 16-17, 2013).

Myusic: a Content-based Music Recommender System based on eVSM and Social Media

Fedelucio Narducci;
2013-01-01

Abstract

This paper presents Myusic, a platform that leverages socialmedia to produce content-based music recommendations. The design ofthe platform is based on the insight that user preferences in music canbe extracted by mining Facebook profiles, thus providing a novel and ef-fective way to sift in large music databases and overcome the cold-startproblem as well. The content-based recommendation model implementedin Myusic is eVSM [4], an enhanced version of the vector space modelbased on distributional models, Random Indexing and Quantum Nega-tion. The effectiveness of the platform is evaluated through a preliminaryuser study performed on a sample of 50 persons. The results showed that74% of users actually prefer recommendations computed by social media-based profiles with respect to those computed by a simple heuristic basedon the popularity of artists, and confirmed the usefulness of performinguser studies because of the different outcomes they can provide withrespect to offline experiments.
2013
4th Italian Information Retrieval Workshop, IIR 2013
Myusic: a Content-based Music Recommender System based on eVSM and Social Media / Musto, Cataldo; Narducci, Fedelucio; Semeraro, Giovanni; Lops, Pasquale; de Gemmis, Marco. - ELETTRONICO. - 964:(2013), pp. 65-72. (Intervento presentato al convegno 4th Italian Information Retrieval Workshop, IIR 2013 tenutosi a Pisa, Italy nel January 16-17, 2013).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/215919
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