Discovering and Visualizing Prototypical Artists by Web-based Co-occurrence Analysis

Description

Detecting artists that can be considered as prototypes for particular genres or styles of music is an interesting task. In this paper, we present an approach that ranks artists according to their prototypicality. To calculate such a ranking, we use asymmetric similarity matrices obtained via co-occurrence analysis of artist names on web pages. We demonstrate our approach on a data set containing 224 artists from 14 genres and evaluate the results using the rank correlation between the prototypicality ranking and a ranking obtained by page counts of search queries to Google that contain artist and genre. High positive rank correlations are achieved for nearly all genres of the data set. Furthermore, we elaborate a visualization method that illustrates similarities between artists using the prototypes of all genres as reference points. On the whole, we show how to create a prototypicality ranking and use it, together with a similarity matrix, to visualize a music repository

Period	11 Sept 2005
Event title	6th International Conference on Music Information Retrieval (ISMIR 2005), London, UK
Event type	Conference
Location	United KingdomShow on map