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author | Paulo Chiliguano <p.e.chiliguano@se14.qmul.ac.uk> |
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date | Sat, 09 Jul 2022 00:50:43 -0500 |
parents | fcd3730ffc19 |
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\section{Hybrid Music Recommender} The hybrid music recommender approach is an implementation of feature augmentation and meta-level methods. One advantage of the meta-level method is the use of compressed users and songs information instead of sparse raw data. %\begin{itemize} %\item We model bananas and plums using a density estimation of the colour space. %\item We fit a Gaussian Mixture Model using Expectation Maximization. We select the number of clusters using an MDL criteria. %\item Typical image examples of bananas and plums look like this: %\end{itemize} \begin{center} \resizebox*{0.9\columnwidth}{!}{\includegraphics{images/diagram_hybrid_music_recommender.eps}}\\ {\large \textbf{Fig. 1.} Diagram of our hybrid music recommender approach} %\begin{tabular}{c@{ }c} %\resizebox*{0.45\columnwidth}{!}{\includegraphics{images/diagram_hybrid_music_recommender.eps}} & %\resizebox*{0.45\columnwidth}{!}{\includegraphics{images/fruit/plums.eps}} \\ %Bananas & Plums \\ %\end{tabular} \end{center}