view Report/chiliguano_msc_finalproject.toc @ 26:e4bcfe00abf4

Final version of code

\contentsline {chapter}{\numberline {1}Introduction}{1}{chapter.1}
\contentsline {section}{\numberline {1.1}Motivation}{2}{section.1.1}
\contentsline {section}{\numberline {1.2}Aim}{3}{section.1.2}
\contentsline {section}{\numberline {1.3}Outline of the thesis}{4}{section.1.3}
\contentsline {chapter}{\numberline {2}Background}{5}{chapter.2}
\contentsline {section}{\numberline {2.1}Online Social Networks}{6}{section.2.1}
\contentsline {subsection}{\numberline {2.1.1}Last.fm}{6}{subsection.2.1.1}
\contentsline {section}{\numberline {2.2}Music services platforms}{7}{section.2.2}
\contentsline {subsection}{\numberline {2.2.1}Echonest}{7}{subsection.2.2.1}
\contentsline {subsection}{\numberline {2.2.2}7Digital}{7}{subsection.2.2.2}
\contentsline {section}{\numberline {2.3}Recommender Systems}{7}{section.2.3}
\contentsline {subsection}{\numberline {2.3.1}Collaborative filtering}{7}{subsection.2.3.1}
\contentsline {subsection}{\numberline {2.3.2}Content-based methods}{8}{subsection.2.3.2}
\contentsline {section}{\numberline {2.4}Hybrid recommender methods}{8}{section.2.4}
\contentsline {section}{\numberline {2.5}Music Information Retrieval}{8}{section.2.5}
\contentsline {subsection}{\numberline {2.5.1}Musical genre classification}{8}{subsection.2.5.1}
\contentsline {subsection}{\numberline {2.5.2}Deep Learning}{9}{subsection.2.5.2}
\contentsline {subsection}{\numberline {2.5.3}Convolutional Neural Networks}{9}{subsection.2.5.3}
\contentsline {section}{\numberline {2.6}Estimation of Distribution Algorithms}{10}{section.2.6}
\contentsline {chapter}{\numberline {3}Methodology}{11}{chapter.3}
\contentsline {section}{\numberline {3.1}Data collection}{11}{section.3.1}
\contentsline {subsection}{\numberline {3.1.1}Taste Profile subset cleaning}{12}{subsection.3.1.1}
\contentsline {subsection}{\numberline {3.1.2}Audio clips retrieval}{12}{subsection.3.1.2}
\contentsline {subsection}{\numberline {3.1.3}Intermediate time-frequency representation for audio signals}{13}{subsection.3.1.3}
\contentsline {section}{\numberline {3.2}Data preprocessing}{13}{section.3.2}
\contentsline {section}{\numberline {3.3}Algorithms}{14}{section.3.3}
\contentsline {subsection}{\numberline {3.3.1}CNN architecture}{14}{subsection.3.3.1}
\contentsline {subsubsection}{Genre classification}{14}{section*.5}
\contentsline {subsection}{\numberline {3.3.2}Continuous Bayesian EDA}{14}{subsection.3.3.2}
\contentsline {subsection}{\numberline {3.3.3}EDA-based hybrid recommender}{14}{subsection.3.3.3}
\contentsline {chapter}{\numberline {4}Experiments}{15}{chapter.4}
\contentsline {section}{\numberline {4.1}Evaluation for recommender systems}{15}{section.4.1}
\contentsline {subsection}{\numberline {4.1.1}Types of experiments}{15}{subsection.4.1.1}
\contentsline {section}{\numberline {4.2}Evaluation method}{17}{section.4.2}
\contentsline {subsection}{\numberline {4.2.1}Dataset description}{17}{subsection.4.2.1}
\contentsline {subsection}{\numberline {4.2.2}Evaluation measures}{17}{subsection.4.2.2}
\contentsline {chapter}{\numberline {5}Results}{18}{chapter.5}
\contentsline {chapter}{\numberline {6}Conclusion}{20}{chapter.6}
\contentsline {section}{\numberline {6.1}Future work}{20}{section.6.1}