Abstract
In this paper, we present a mobile recommender system for music. The system acts as middleware that facilitates the recommendation in push technologybased mobile services and combines content-based retrieval and collaborative filtering. Specifically, a mobile user is provided with the ability to query for music files that belong to the same genre by simply sending an example music file from his/her mobile device. The system recommends to the user music files not only on the basis of acoustic content similarity, but also incorporates collaborative filtering techniques in order to offer more personalized recommendations.
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Lampropoulou, P.S., Lampropoulos, A.S., Tsihrintzis, G.A. (2009). A Mobile Music Recommender System based on a Two-level Genre-Rating SVM Classifier enhanced by Collaborative Filtering. In: Damiani, E., Jeong, J., Howlett, R.J., Jain, L.C. (eds) New Directions in Intelligent Interactive Multimedia Systems and Services - 2. Studies in Computational Intelligence, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02937-0_33
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DOI: https://doi.org/10.1007/978-3-642-02937-0_33
Publisher Name: Springer, Berlin, Heidelberg
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