Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
An Empirical Analysis of Network Externalities in Peer-to-Peer Music-Sharing Networks
Information Systems Research
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
Toward Virtual Community Knowledge Evolution
Journal of Management Information Systems
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The music industry's business model is to produce stars. In order to do so, musicians producing music that fits into well defined clusters of factors explaining the demand of the majority of music consumers are disproportionately promoted. This leads to a limitation of available diversity and therefore of a limitation of the end user's benefit from listening to music. This paper analyses online music consumer's needs and preferences. These factors are used in order to explain the demand for stars and the impact of different online music services on promoting a more diverse music market.