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MESSAGE FOLLOWS:
Dear all,
A reminder that tomorrow at 2:30pm, Markus Schedl will present the
seminar 'The (Social) Web and Music, Stars and the Like'.
The seminar will take place in room 105 in the Electronic
Engineering building, Queen Mary University of London, Mile End
Road, London E1 4NS. The Electronic Engineering building can be
accessed using the glass entrance from Mile End Road, which is
located next to the bus stop 'Queen Mary, University of London'
(buses 25, 205). The room is under access control, so people from
outside QM will need to contact C4DM to get in - the lab phone
number is +44 (0)20 7882 7480 and if I'm not available, anyone
else in the lab should be able to help. If you are coming from
outside Queen Mary, please let me know, so I can make sure
no-one's stuck outside the doors. Details of future seminars can
be found at
http://www.eecs.qmul.ac.uk/newsevents/researchgroupevents.php?i=12.
All are welcome to attend. For those unable to do so, a video
recording of the seminar will be streamed live and also made
available online after a few days. Please see the above website
for details.
If you wish to be added to / removed from our mailing list, please
send me an email and I'll be happy to do so.
Tomorrow's seminar (2 March, 2:30pm):
Title:
The (Social) Web and Music, Stars and the Like
Speaker:
Markus Schedl (Johannes Kepler University Linz)
Abstract:
Music context-based information extraction is a hot research
topic, not at least because of the enormous rise Social Web usage
has encountered during the last couple of years. In this seminar
talk, I will present Web-based methods to extract data about music
entities (mostly on the level of music artists) and show how such
data can be used to build music applications and services. The
talk will cover three areas of Web-based MIR:
- music-related information extraction (How to automatically build
a music information system?)
- artist similarity measurement using Web pages and using
microblogs (tweets)
- popularity estimation (Who's hot?)
For the first topic, I will report on text-based information
extraction methods to determine prototypical artists with respect
to a certain category (e.g., genre), to perform automated tagging,
to retrieve album cover artwork, and to detect band members and
instrumentation. As for the similarity measurement task, I will
report on large-scale evaluation experiments aimed at determining
well-performing parameter settings for modeling the Web-based
music similarity space (e.g., TF-, IDF-formulations, normalization
strategies, similarity functions). Finally, I will present and
compare different techniques to predicting the popularity of a
music artist using different data sources (Web, Twitter, last.fm,
Peer-to-Peer Networks).
Bio:
Markus Schedl graduated in Computer Science from the Vienna
University of Technology. He earned his Ph.D. in Computational
Perception from the Johannes Kepler University Linz, where he is
employed as assistant professor at the Department of Computational
Perception. He further holds a Master's degree in International
Business Administration from the Vienna University of Economics
and Business Administration. Schedl (co-)authored more than 40
refereed conference papers and several journal articles.
Furthermore, he reviewed submissions to various conferences and
articles for the journals IEEE Transactions on Multimedia and
Springer Multimedia Systems, as well as for the IEEE
Communications Magazine. He is co-founder of the International
Workshop on Advances in Music Information Research. His main
research interests include Web Mining, Music and Multimedia
Information Retrieval, Information Visualization, and
Recommendation/Personalization.
Emmanouil Benetos
--
Centre for Digital Music (C4DM)
School of Electronic Engineering and Computer Science
Queen Mary, University of London
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Tel: +44 (0)20 7882 7480
Fax: +44 (0)20 7882 7997
C4DM Web-site : http://www.elec.qmul.ac.uk/digitalmusic/index.html