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Department of
Computational
Perception
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Automatically Generated Music
Information System (AGMIS)
Music-related information is becoming more and more important in times
of digital music distribution via the Internet as users of online music
stores nowadays expect to be offered additional meta-information beyond
the pure digital music file. The AGMIS project aims at developing novel
techniques as well as refining existing ones in order to gather
information about music artists and bands from the Web. More precisely,
on sets of Web pages that are related to a music artist or band, Web
content mining techniques are applied to extract the following
categories of information:
• similarities between music artists or bands
• prototypicality of an artist or a band for a genre
• descriptive properties of an artist or a band
• band members and instrumentation
• images of album cover artwork
AGMIS demonstrates the applicability of the elaborated techniques on a
large collection of more than 600,000 artists by providing a Web-based
user interface to access a database that has been populated
automatically with the extracted information. Although AGMIS does not
always give perfectly accurate results, the automatic approaches to
information retrieval have some advantages in comparison with those
employed in existing music information systems, which are either based
on labor-intensive information processing by music experts or on
community knowledge that is vulnerable to distortion of information.
A prototypical implementation of AGMIS is running as Java servlet at dragonforce.cp.jku.at:8180/AGMIS/search.
Please be aware that the service may be down for some reason.
References
Automatically Extracting, Analyzing, and Visualizing
Information on Music Artists from the World Wide Web
Schedl, M.
PhD Thesis. Johannes Kepler University Linz, June 2008.
>> PDF, BibTeX
Towards an
Automatically Generated Music Information System via Web Content Mining
Schedl, M., Knees, P., Pohle, T., and Widmer, G.
Proceedings of the 30th European Conference on Information Retrieval
(ECIR 2008), Glasgow, Scotland, March-April 2008.
© Springer-Verlag, Published in the Lecture Notes in Computer Science (LNCS)
series.
>> PDF, BibTeX
last edited
by ms
at
2008-09-30