Music-related metadata is becoming more and more important in times
of digital music distribution. Methods for automatically extracting
such information from the WWW have been elaborated, implemented,
and analyzed. On sets of Web pages that are related to a music
artist or band, Web content mining techniques are applied to
address the following categories of information: similarities
between music artists, prototypicality of an artist for a genre,
descriptive properties of an artist, band members and
instrumentation, images of album cover artwork. Different
approaches to retrieve the corresponding pieces of information for
each of these categories have been elaborated and evaluated
thoroughly on a considerable variety of music repositories.
Moreover, visualization methods and user interaction models for
prototypical and similar artists as well as for descriptive terms
will be presented. Based on the insights gained by the conducted
experiments, the core application of this thesis, the Automatically
Generated Music Information System (AGMIS) was build. AGMIS
demonstrates the applicability of the elaborated techniques on a
large collection of more than 600,000 artists.
General
Imprint: |
VDM Verlag Dr. Mueller E.K.
|
Country of origin: |
Germany |
Release date: |
October 2008 |
First published: |
October 2008 |
Authors: |
Markus Schedl
|
Dimensions: |
229 x 152 x 9mm (L x W x T) |
Format: |
Paperback - Trade
|
Pages: |
172 |
ISBN-13: |
978-3-8381-0082-1 |
Categories: |
Books >
Computing & IT >
Internet >
General
|
LSN: |
3-8381-0082-4 |
Barcode: |
9783838100821 |
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