6,589 research outputs found
The Skipping Behavior of Users of Music Streaming Services and its Relation to Musical Structure
The behavior of users of music streaming services is investigated from the
point of view of the temporal dimension of individual songs; specifically, the
main object of the analysis is the point in time within a song at which users
stop listening and start streaming another song ("skip"). The main contribution
of this study is the ascertainment of a correlation between the distribution in
time of skipping events and the musical structure of songs. It is also shown
that such distribution is not only specific to the individual songs, but also
independent of the cohort of users and, under stationary conditions, date of
observation. Finally, user behavioral data is used to train a predictor of the
musical structure of a song solely from its acoustic content; it is shown that
the use of such data, available in large quantities to music streaming
services, yields significant improvements in accuracy over the customary
fashion of training this class of algorithms, in which only smaller amounts of
hand-labeled data are available
User evaluation outside the lab: the trial of FĂschlár-News
A user study of FĂschlár-News system was conducted in Spring 2004 with 16 users, each user using the system for a 1-month period. FĂschlár-News is an experimental online news archive that incorporates various automatic content-based video indexing techniques and a news story recommender algorithm to process and index the daily 9 o’clock broadcast news from TV and allows its users to browse, search, be recommended, and play news stories on a conventional web browser. Pre and post-trial questionnaires, interaction logging and incident diary methods collected both qualitative and quantitative usage data during the trial period. While the details of the findings from this evaluation is reported elsewhere, in this paper we report the details of the methodology taken and our experience of conducting this evaluation
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