Markus Schedl, Christine Bauer,
"Introducing Global and Regional Mainstreaminess for Improving Personalized Music Recommendation"
: Proceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2017), 12-2017
Introducing Global and Regional Mainstreaminess for Improving Personalized Music Recommendation
Sprache des Titels:
Proceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2017)
The music mainstreaminess of a user reflects how strong a user?s
listening preferences correspond to those of the larger population.
Considering that music mainstream may be defined from different
perspectives and on various levels, e.g., geographical (charts
of a country), genre (?Indie charts"), or distribution channel (radio
charts vs. download charts), we study how the user?s music
mainstreaminess influences the quality of music recommendations.
The paper?s contribution is three-fold. First, we propose 11 novel
mainstreaminess measures characterizing music listeners, considering
both a global and a country-specific basis. To this end, we model
preference profiles (as a vector over artists) for users, countries, and
globally, incorporating artist frequency, listener frequency, and a
newly proposed TF-IDF-inspired weighting function, which we call
artist frequency?inverse listener frequency (AF-ILF). The resulting
preference profile for each user u is then related to the respective
country-specific and global preference profile using fractionbased
approaches, symmetrized Kullback-Leibler divergence, and
Kendall?s ? rank correlation, in order to quantify u?s mainstreaminess.
Second, we demonstrate country-specific peculiarities of these
mainstreaminess definitions. Third, we show that incorporating
the proposed global and country-specific mainstreaminess measures
into the music recommendation process can notably improve
accuracy of rating prediction.