Automatically Detecting Members and Instrumentation of Music Bands Via Web Content Mining

  • Markus Schedl
  • Gerhard Widmer
Conference paper

DOI: 10.1007/978-3-540-79860-6_10

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4918)
Cite this paper as:
Schedl M., Widmer G. (2008) Automatically Detecting Members and Instrumentation of Music Bands Via Web Content Mining. In: Boujemaa N., Detyniecki M., Nürnberger A. (eds) Adaptive Multimedia Retrieval: Retrieval, User, and Semantics. AMR 2007. Lecture Notes in Computer Science, vol 4918. Springer, Berlin, Heidelberg

Abstract

In this paper, we present an approach to automatically detecting music band members and instrumentation using web content mining techniques. To this end, we combine a named entity detection method with a rule-based linguistic text analysis approach extended by a rule filtering step. We report on the results of different evaluation experiments carried out on two test collections of bands covering a wide range of popularities. The performance of the proposed approach is evaluated using precision and recall measures. We further investigate the influence of different query schemes for the web page retrieval, of a critical parameter used in the rule filtering step, and of different string matching functions which are applied to deal with inconsistent spelling of band members.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Markus Schedl
    • 1
  • Gerhard Widmer
    • 1
    • 2
  1. 1.Department of Computational PerceptionJohannes Kepler UniversityLinzAustria
  2. 2.Austrian Research Institute for Artificial IntelligenceViennaAustria

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