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View Code? Open in Web Editor NEWA RNN-LM-based model for playlist generation with reinforcement learning (ISMIR 2018)
A RNN-LM-based model for playlist generation with reinforcement learning (ISMIR 2018)
The data util script makes use of a vocabulary file that is created started from the raw_dat.txt
([date_of_created_playlist] [song_id1] [song_id2]...
format) file. Is that correct?
And what about creating embedding? How shall I extract it from the song info?
According to the paper
With the users and songs graph, we can
calculate embedding features of songs and thus obtain the
baseline playlist for each songs by finding their k-nearest
neighbors.
Does this mean that I can use low-level or high-level song features? Maybe the spectrum?
Thank you.
Hello, according to the reference paper the first step is about to generate baseline playlists based on the preferences of users about songs. Now assumed that the paper makes use of KKBox dataset, while here the dataset format has been specified, where shall I put user_id
for each song_id
i.e. the user listening?
Thank you.
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