Markus Schedl, David Hauger, J. Urbano,
"Harvesting Microblogs for Contextual Music Similarity Estimation - A Co-occurrence-based Framework"
, in Multimedia Systems, 2013, ISSN: 1432-1882
Original Titel:
Harvesting Microblogs for Contextual Music Similarity Estimation - A Co-occurrence-based Framework
Sprache des Titels:
Englisch
Original Kurzfassung:
Microtexts are a valuable, albeit noisy, source
to infer collaborative information. As music plays an
important role in many human lives, microblogs on musicrelated
activities are available in abundance. This paper
investigates different strategies to estimate music similarity
from these data sources. In particular, we first present a
framework to extract co-occurrence scores between music
artists from microblogs and then investigate 12 similarity
estimation functions to subsequently derive resemblance
scores. We evaluate the approaches on a collection of
microblogs crawled from Twitter over a period of
10 months and compare them to standard tf-idf approaches.
As evaluation criteria we use precision and recall in an
artist retrieval task as well as rank proximity. We show that
collaborative chatter on music can be effectively used to
develop music artist similarity measures, which are a core
part of every music retrieval and recommendation system.
Furthermore, we analyze the effects of the ??long tail?? on
retrieval results and investigate whether results are consistent
over time, using a second dataset
Forschungs-