{"action":"created","comment":{"url":"https://api.github.com/repos/MoodCat/MoodCat.me/pulls/comments/29866147","id":29866147,"diff_hunk":"@@ -0,0 +1,146 @@\n+\n+\\subsection{Functional requirements}\n+For the product MoodCat, the requirements regarding functionality and service are grouped under the \\emph{Functional requirements}.\n+Within these functional requirements, four categories can be identified using the \\emph{MoSCoW} model \\footnote{\\url{http://en.wikipedia.org/wiki/MoSCoW_method}} for prioritizing requirements:\n+\n+\\subsubsection{Must haves}\n+\\begin{itemize}\n+\\item The user shall interact with the product via a web interface.\n+\n+\\item The web interface shall show a screen to log in to the application.\n+\n+\\item The login mechanism shall be managed by SoundCloud OAuth keys (\"Log in with SoundCloud\").\n+\n+\\item The login mechanism shall show an error page when the user does not authorize MoodCat to have access to their SoundCloud data.\n+\n+\\item The web interface shall show a first-use tutorial upon logging in succesfully for the first time.\n+\n+\\item The web interface shall show the user a page where they can select their current mood.\n+\n+\\item The web interface shall show the following moods:\n+\t\t\\begin{itemize}\n+\t\t\\item Nervous\n+\t\t\\item Exiting\n+\t\t\\item Happy\n+\t\t\\item Pleasing\n+\t\t\\item Relaxing\n+\t\t\\item Peaceful\n+\t\t\\item Calm\n+\t\t\\item Sleepy\n+\t\t\\item Bored\n+\t\t\\item Sad\n+\t\t\\end{itemize}\n+\t  These moods are defined by the Arousal/Valence model\\footnote{Y. Chang and H.H. Chen. Music Emotion Recognition. Boca raton, State:\n+CRC Press, 2011.}.\n+\n+\\item The system shall serve the user a list of rooms, ordered by how close they match the given mood.\n+\n+\\item The web interface shall present the user with a room when it is chosen.\n+\t\n+\\item The system shall stream the music from the SoundCloud platform using the SoundCloud API\\footnote{\\url{https://developers.soundcloud.com/docs/api/guide}}\n+\n+\\item The system shall use a multi-layer perceptron system to predict the mood of a song.\n+\n+\\item The system will use a recommender system to determine the next song to be played in each room.\n+\n+\\end{itemize}\n+\\subsubsection{Should haves}\n+\\begin{itemize}\n+\\item The web interface shall start playing the current song on the current timestamp when a user joins the room.\n+\n+\\item A room shall contain a chat, connecting people with the same mood together.\n+\n+\\item A room shall contain a now playing slider.\n+\n+\\item The web interface shall give the user the option to mute the playing music.\n+\n+\\item The web interface shall notify the user if they made an illogical combination of moods, warning them results may vary.\n+\n+\\item A room has a button to upvote the current song, indicating the song is a good fit to the room.\n+\n+\\item A room has a button to downvote the current song, indicating the song is a bad fit to the room. This will also vote to skip.\n+\n+\\item A room has a button to \"vote to skip\". This does not affect the fit of the song to the room, but is a tool to skip songs.\n+\n+\\item A song shall be skipped in one of the following situations:\n+\t\\begin{itemize}\n+\t\\item The song received $\\frac{\\$number\\_of\\_users\\_in\\_room}{3}$ votes to skip.\n+\t\\item The song received at least 10 votes, and the ratio upvote:downvote is 1:2 or less.\n+\t\\item A moderator skips the song (to prevent escalations)\n+\t\\end{itemize}\n+\t\n+\\item The system shall periodically suggest the user to hop to another room to encourage more interaction and we can direct the user to a more preferred mood.\n+\n+\\item The multi-layer perceptron shall be trained with metadata provided by EEMCS","path":"Documentation/General/productPlanning/requirements.tex","position":74,"original_position":74,"commit_id":"11e9b9034434c869f662b12ab684da4c1d25b9b0","original_commit_id":"11e9b9034434c869f662b12ab684da4c1d25b9b0","user":{"login":"JWGmeligMeyling","id":3469492,"avatar_url":"https://avatars.githubusercontent.com/u/3469492?v=3","gravatar_id":"","url":"https://api.github.com/users/JWGmeligMeyling","html_url":"https://github.com/JWGmeligMeyling","followers_url":"https://api.github.com/users/JWGmeligMeyling/followers","following_url":"https://api.github.com/users/JWGmeligMeyling/following{/other_user}","gists_url":"https://api.github.com/users/JWGmeligMeyling/gists{/gist_id}","starred_url":"https://api.github.com/users/JWGmeligMeyling/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/JWGmeligMeyling/subscriptions","organizations_url":"https://api.github.com/users/JWGmeligMeyling/orgs","repos_url":"https://api.github.com/users/JWGmeligMeyling/repos","events_url":"https://api.github.com/users/JWGmeligMeyling/events{/privacy}","received_events_url":"https://api.github.com/users/JWGmeligMeyling/received_events","type":"User","site_admin":false},"body":"It will be trained by the users. The data is not from EEMCS (Friso comments). I would go for\r\n\r\n> The systems cold start will be enabled by generating initial values from the metadata in our 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