Automatic Classification of Musical Artists based on Web-Data
Sprache des Titels:
The organization of music is one of the central challenges in times of increasing distribution
of digital music. A well-tried means is the classification in genres and/or styles. In
this paper we propose the use of text categorization techniques to classify artists present
on the Internet. In particular, we retrieve and analyze webpages ranked by search engines
to describe artists in terms of word occurrences on related pages. To classify artists
we primarily use support vector machines.
Based on a previously published paper and on a master’s thesis, we present experiments
comprising the evaluation of the classification process on a taxonomy of 14 genres with
altogether 224 artists, as well as an estimation of the impact of daily fluctuations in the
Internet on our approach, exploiting a long-term study over a period of almost one year.
On the basis of these experiments we study (a) how many artists are necessary to define
the concept of a genre, (b) which search engines perform best, (c) how to formulate
search queries best, (d) which overall performance we can expect for classification, and
finally (e) how our approach is suited as a similarity measure for artists.
Sprache der Kurzfassung:
ÖGAI Journal 24/1
Anzahl der Seiten:
Aufsatz / Paper in sonstiger referierter Fachzeitschrift