2 research outputs found
People know how diverse their music recommendations should be; why don’t we?
While many researchers have proposed various ways of quantifying recommendation
list diversity, these approaches have had little input from users on their own perceptions
and preferences in seeking diversity. Through a set of user studies we provide a better
understanding of how users view the concept of diversity in music recommendations, and
how intra-list diversity can be adapted to better represent their diversity preference. Our
results show that users have a clear idea of what music recommendation diversity means to
them, accuracy metrics do not model overall list satisfaction, and filtering recommendations
on genre before list diversification can positively impact list satisfaction. More importantly,
our results highlight the need to base music recommendation metrics on insights from real
peopl