16th International Conference on Intelligent User Interfaces (IUI 201
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Music retrieval systems that take into account the user?s taste
and information or entertainment need when building the results
set to a query are of vital interest for academia, industry,
and the passionate music listener. Unfortunately, preliminary
attempts to incorporate such aspects have been rather
sparse so far. Focusing on the problem of music recommendation,
we therefore present a new model that combines several
factors we deem to be important for personalizing retrieval
results: similarity, diversity, popularity, hotness, recentness,
novelty, and serendipity. We further propose different
ways to measure the corresponding aspects and, where
available, point to literature for a more detailed elaboration of
the corresponding measures. In addition, we propose the use
of social media mining techniques to address the problem of
estimating popularity and hotness in a geo-aware manner.
Forschungs-