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- W3156091632 abstract "Fairness is an important aspect in group recommender systems (GRSs). They must ensure that potentially diverse preferences of all group members are taken into consideration when providing recommendations. Previous work has proposed a number of conflict elicitation and merging techniques to produce preferable recommendations for group members. However, we have yet to understand the influence of user personality on the perception of fairness in GRSs. To examine this gap, we use music recommendation as an example domain. We have developed a web-based group music recommender system using the Spotify API and two simple ranking algorithms: one based on the time the songs were voted by users (time-based) and the other based on a dissimilarity score (dissimilarity-based). A within-subjects experiment was conducted with 45 participants divided into groups of 3 (15 groups). Results showed that openness personality has a negative correlation with the perception that fairness is important in groups." @default.
- W3156091632 created "2021-04-26" @default.
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- W3156091632 date "2021-04-14" @default.
- W3156091632 modified "2023-10-18" @default.
- W3156091632 title "Perception of Fairness in Group Music Recommender Systems" @default.
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- W3156091632 doi "https://doi.org/10.1145/3397481.3450642" @default.
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