\chapter{Methodology}
\section{Data collection}
\subsection{Taste profile subset filtering}
%At this stage, similarities between users is calculated to form a neighbourhood and predict user rating based on combination of the ratings of selected users in the neighbourhood.
\subsection{Audio samples collection}
%Classifier creates a model for each user based on the acoustic features of the tracks that user has liked.
\subsection{Log-mel spectrograms}

\section{Algorithms}
\subsection{CNN implementation}
%Deep belief network is a probabilistic model that has one observed layer and several hidden layers.
\subsubsection{Genre classification}

\subsection{Continuous Bayesian EDA}
\subsection{EDA-based hybrid recommender}