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Leveraging social media sources to generate personalized music playlists
Abstract This paper presents MyMusic, a system thatThis 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. Specifically, 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.sults encouraged keeping on this research.
Abstractsub This paper presents MyMusic, a system thatThis 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. Specifically, 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.sults encouraged keeping on this research.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-32273-0_10  +
Has author Musto C. + , Giovanni Semeraro + , Pasquale Lops + , De Gemmis M. + , Narducci F. +
Has extra keyword Cold start problems + , Content-based + , DBpedia + , Enrichment techniques + , Facebook + , Last.fm + , Music recommendation + , Personalizations + , Prototype versions + , Social media + , Social Networks + , User interests + , User study + , Wikipedia + , Social networking (online) + , Starting + , Electronic commerce +
Has keyword DBpedia + , Music Recommendation + , Personalization + , Social Media +
Isbn 9783642322723  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 112–123  +
Published in Lecture Notes in Business Information Processing +
Title Leveraging social media sources to generate personalized music playlists +
Type conference paper  +
Volume 123 LNBIP  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 8 November 2014 03:42:28  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 8 November 2014 03:42:28  +
DateThis property is a special property in this wiki. 2012  +
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