Markus Schedl, Dominik Schnitzer,
"Hybrid Retrieval Approaches to Geospatial Music Recommendation."
: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2013), 7-2013
Hybrid Retrieval Approaches to Geospatial Music Recommendation.
Sprache des Titels:
Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2013)
Recent advances in music retrieval and
recommendation algorithms highlight the necessity to follow multimodal approaches
in order to transcend limits imposed by methods
that solely use audio, web, or collaborative filtering data. In
this paper, we propose hybrid music recommendation algorithms
that combine information on the music content, the
music context, and the user context, in particular, integrating
location-aware weighting of similarities. Using state-of-the-art
techniques to extract audio features and contextual
web features, and a novel standardized data set of music listening
activities inferred from microblogs (MusicMicro), we
propose several multimodal retrieval functions.
The main contributions of this paper are (i) a systematic
evaluation of mixture coefficients between state-of-the-art
audio features and web features, using the first standardized
microblog data set of music listening events for retrieval
purposes and (ii) novel geospatial music recommendation
approaches using location information of microblog users,
and a comprehensive evaluation thereof.