Abstract
Music services, media players and managers provide support for content classification and access based on filtering metadata values, statistics of access, and user ratings. This approach fails to capture characteristics of mood and personal history that are often the deciding factor when creating personal playlists and collections in music. This paper presents MusicWiz, a music management environment that combines traditional metadata with spatial hypertext-based expression and automatically extracted characteristics of music to generate personalized associations between songs. MusicWiz’s similarity inference engine combines the personal expression in the workspace with assessments of similarity based on the artists, other metadata, lyrics, and the audio signal to make suggestions and to generate playlists. An evaluation of MusicWiz with and without the workspace and suggestion capabilities showed significant differences for organizing and playlist creation tasks. The workspace features were more valuable for organizing tasks while the suggestion features had more value for playlist creation activities.
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Meintanis, K., Shipman, F.M. (2010). Visual Expression for Organizing and Accessing Music Collections in MusicWiz. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2010. Lecture Notes in Computer Science, vol 6273. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15464-5_10
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DOI: https://doi.org/10.1007/978-3-642-15464-5_10
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