Sequential skip prediction
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Benchmarks
MSSD
Most implemented
Sequential modeling of Sessions using Recurrent Neural Networks for Skip Prediction
Skip prediction using boosting trees based on acoustic features of tracks in sessions
Modelling Sequential Music Track Skips using a Multi-RNN Approach
Sequential Skip Prediction with Few-shot in Streamed Music Contents
Papers
Sequential modeling of Sessions using Recurrent Neural Networks for Skip Prediction
Recommender systems play an essential role in music streaming services, prominently in the form of personalized playlists. Exploring the user interactions within these listening sessions can be beneficial to understandin…
DecoderPositionRecommendation SystemsSequential skip predictionSkip prediction using boosting trees based on acoustic features of tracks in sessions
The Spotify Sequential Skip Prediction Challenge focuses on predicting if a track in a session will be skipped by the user or not. In this paper, we describe our approach to this problem and the final system that was sub…
Sequential skip predictionModelling Sequential Music Track Skips using a Multi-RNN Approach
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.…
Sequential skip predictionSession-based Sequential Skip Prediction via Recurrent Neural Networks
The focus of WSDM cup 2019 is session-based sequential skip prediction, i.e. predicting whether users will skip tracks, given their immediately preceding interactions in their listening session. This paper provides the s…
PredictionSequential skip predictionSession-Based RecommendationsSequential Skip Prediction with Few-shot in Streamed Music Contents
This paper provides an outline of the algorithms submitted for the WSDM Cup 2019 Spotify Sequential Skip Prediction Challenge (team name: mimbres). In the challenge, complete information including acoustic features and u…
Few-Shot LearningMeta-LearningMetric LearningSequential skip prediction