Michael Vötter

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 10

Top Topics

Recurrent Neural Networks

Prediction Accuracy

Learning To Rank

Top Venues

Grundlagen von Datenbanken

Publications

Maximilian Mayerl, Michael Vötter, Günther Specht, Eva Zangerle
Pairwise Learning to Rank for Hit Song Prediction. BTW (2023)
Michael Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle
HSP Datasets: Insights on Song Popularity Prediction. Int. J. Semantic Comput. 16 (2) (2022)
Michael Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle
Novel Datasets for Evaluating Song Popularity Prediction Tasks. ISM (2021)
Maximilian Mayerl, Michael Vötter, Andreas Peintner, Günther Specht, Eva Zangerle
Recognizing Song Mood and Theme: Clustering-based Ensembles. MediaEval (2021)
Michael Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle
Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups. MediaEval (2020)
Michael Vötter, Eva Zangerle, Maximilian Mayerl, Günther Specht
Autoencoders for Next-Track-Recommendation. Grundlagen von Datenbanken (2019)
Hsiao-Tzu Hung, Yu-Hua Chen, Maximilian Mayerl, Michael Vötter, Eva Zangerle, Yi-Hsuan Yang
MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach. MediaEval (2019)
Maximilian Mayerl, Michael Vötter, Eva Zangerle, Günther Specht
Language Models for Next-Track Music Recommendation. Grundlagen von Datenbanken (2019)
Eva Zangerle, Michael Vötter, Ramona Huber, Yi-Hsuan Yang
Hit Song Prediction: Leveraging Low- and High-Level Audio Features. ISMIR (2019)
Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Bo-Yu Chen, Yi-Hsuan Yang, Eva Zangerle
Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks. MediaEval (2019)