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Investigating gender fairness of recommendation algorithms in the music domain.

, , , , , and . Inf. Process. Manag., 58 (5): 102666 (2021)

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Investigating gender fairness of recommendation algorithms in the music domain., , , , , and . Inf. Process. Manag., 58 (5): 102666 (2021)Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?, , , , , , and . RecSys, page 601-606. ACM, (2021)EmoMTB: Emotion-aware Music Tower Blocks., , , , , , , , and . ICMR, page 206-210. ACM, (2022)Explainability in Music Recommender Systems., , , , , and . CoRR, (2022)Personality Bias of Music Recommendation Algorithms., , and . RecSys, page 533-538. ACM, (2020)Pandemics, music, and collective sentiment: evidence from the outbreak of COVID-19., , , , and . ISMIR, page 157-165. (2020)Personality Correlates of Music Audio Preferences for Modelling Music Listeners., and . UMAP, page 313-317. ACM, (2020)Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation., , , , , , , , and . Int. J. Multim. Inf. Retr., 12 (1): 13 (June 2023)LEMONS: Listenable Explanations for Music recOmmeNder Systems., , , and . ECIR (2), volume 12657 of Lecture Notes in Computer Science, page 531-536. Springer, (2021)Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization., , , , , , and . MORS@RecSys, volume 3268 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)