This article describes a preliminary study on considering information about the target user's personality in music recommender systems (MRSs). For this purpose, we devised and implemented four MRSs and evaluated them on a sample of real users and real-world datasets. Experimental results show that MRSs that rely on purely users' personality information are able to provide performance comparable with those of a state-of-the-art MRS, even better in terms of the diversity of the suggested items.

Onori, M., Micarelli, A., Sansonetti, G. (2016). A comparative analysis of personality-based music recommender systems. In CEUR Workshop Proceedings (pp.55-59). CEUR-WS.

A comparative analysis of personality-based music recommender systems

Micarelli A.;Sansonetti G.
2016-01-01

Abstract

This article describes a preliminary study on considering information about the target user's personality in music recommender systems (MRSs). For this purpose, we devised and implemented four MRSs and evaluated them on a sample of real users and real-world datasets. Experimental results show that MRSs that rely on purely users' personality information are able to provide performance comparable with those of a state-of-the-art MRS, even better in terms of the diversity of the suggested items.
Onori, M., Micarelli, A., Sansonetti, G. (2016). A comparative analysis of personality-based music recommender systems. In CEUR Workshop Proceedings (pp.55-59). CEUR-WS.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/373705
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