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Intelligent User Interfaces for Music Discovery

  • Published:2020 Issue:1 Volume:3 Page:165-179
  • ISSN:2514-3298
  • Container-title:Transactions of the International Society for Music Information Retrieval
  • language:en
  • Short-container-title:

Author:

Knees PeterORCID,Schedl Markus,Goto Masataka

Publisher

Ubiquity Press, Ltd.

Reference116 articles.

1. Moodplay: Interactive music recommendation based on artists’ mood similarity;International Journal of Human-Computer Studies,2019

2. User-centered design of a social game to tag music;Proceedings of the ACM SIGKDD Workshop on Human Computation (HCOMP 2009),2009

3. Augmenting music listening experiences on voice assistants,2019

4. Autotagger: A model for predicting social tags from acoustic features on large music databases;Journal of New Music Research,2008

5. Can all tags be used for search?,2008

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1. Artist Similarity Based on Heterogeneous Graph Neural Networks;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. Kiite Cafe: A Web Service Enabling Users to Listen to the Same Song at the Same Moment While Reacting to the Song;IEICE Transactions on Information and Systems;2023-11-01

3. Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

4. Promoting Music Exploration through Personalized Nudging in a Genre Exploration Recommender;International Journal of Human–Computer Interaction;2022-08-21

5. Explainability in music recommender systems;AI Magazine;2022-06
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