Modelling Sequential Music Track Skips using a Multi-RNN Approach

03/20/2019
by   Christian Hansen, et al.
0

Modelling sequential music skips provides streaming companies the ability to better understand the needs of the user base, resulting in a better user experience by reducing the need to manually skip certain music tracks. This paper describes the solution of the University of Copenhagen DIKU-IR team in the 'Spotify Sequential Skip Prediction Challenge', where the task was to predict the skip behaviour of the second half in a music listening session conditioned on the first half. We model this task using a Multi-RNN approach consisting of two distinct stacked recurrent neural networks, where one network focuses on encoding the first half of the session and the other network focuses on utilizing the encoding to make sequential skip predictions. The encoder network is initialized by a learned session-wide music encoding, and both of them utilize a learned track embedding. Our final model consists of a majority voted ensemble of individually trained models, and ranked 2nd out of 45 participating teams in the competition with a mean average accuracy of 0.641 and an accuracy on the first skip prediction of 0.807. Our code is released at https://github.com/Varyn/WSDM-challenge-2019-spotify.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/23/2019

Sequential modeling of Sessions using Recurrent Neural Networks for Skip Prediction

Recommender systems play an essential role in music streaming services, ...
research
03/28/2019

Skip prediction using boosting trees based on acoustic features of tracks in sessions

The Spotify Sequential Skip Prediction Challenge focuses on predicting i...
research
01/24/2019

Sequential Skip Prediction with Few-shot in Streamed Music Contents

This paper provides an outline of the algorithms submitted for the WSDM ...
research
02/13/2019

Session-based Sequential Skip Prediction via Recurrent Neural Networks

The focus of WSDM cup 2019 is session-based sequential skip prediction, ...
research
02/08/2020

Predict your Click-out: Modeling User-Item Interactions and Session Actions in an Ensemble Learning Fashion

This paper describes the solution of the POLINKS team to the RecSys Chal...
research
04/28/2020

The universality of skipping behaviours on music streaming platforms

A recent study of skipping behaviour on music streaming platforms has sh...
research
07/14/2017

Modeling Harmony with Skip-Grams

String-based (or viewpoint) models of tonal harmony often struggle with ...

Please sign up or login with your details

Forgot password? Click here to reset