Abstract

This paper presents MyMusic, a system that exploits social media sources for generating personalized music playlists. This work is based on the idea that information extracted from social networks, such as Facebook and Last.fm, might be effectively exploited for personalization tasks. Indeed, information related to music preferences of users can be easily gathered from social platforms and used to define a model of user interests. The use of social media is a very cheap and effective way to overcome the classical cold start problem of recommender systems. In this work we enriched social media-based playlists with new artists related to those the user already likes. Specically, we compare two different enrichment techniques: the first leverages the knowledge stored on DBpedia, the structured version of Wikipedia, while the second is based on the content-based similarity between descriptions of artists. The final playlist is ranked and finally presented to the user that can listen to the songs and express her feedbacks. A prototype version of MyMusic was made available online in order to carry out a preliminary user study to evaluate the best enrichment strategy. The preliminary results encouraged keeping on this research.

Autore Pugliese

• Musto Cataldo , Semeraro Giovanni , De Gemmis Marco , Lops Pasquale

Tutti gli autori

• MUSTO C.;NARDUCCI F.;SEMERARO G.;de GEMMIS M.;LOPS P.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2012

ISSN

1865-1348

ISBN

978-3-642-32272-3

Numero di citazioni Wos

7

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

16

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile