Investigating Web-Based Approaches to Revealing Prototypical Music Artists in Genre Taxonomies

We present three general approaches to detecting prototypical entities in a given taxonomy and apply them to a music information retrieval (MIR) problem. More precisely, we try to find prototypical music artists for each genre in a given real-world taxonomy. The three approaches rely on web-based data mining techniques and derive prototypicality rankings from properties based on the number of web pages found for given entity names. We illustrate the approaches using a genre taxonomy created by music experts and present results of extensive evaluations. In detail, three evaluation approaches have been applied. First, we model and evaluate a classification task to determine accuracies. Taking the ordinal character of the prototypicality rankings into account, we further calculate rank order correlation according to Spearman and to Kendall. Interesting insights concerning the performance of the respective approaches when confronting them to the expert rankings are given.