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Browsing Music by Usage Context

This paper aims to motivate and demonstrate how widely available environmental data can be exploited to allow organization, structuring and exploration of music collections by personal listening con- texts. We describe a logging plug-in for music players that automatically records data about the listening context and discuss possible extensions for more sophisticated context logging. Based on data collected in a small user experiment, we show how data mining techniques can be applied to reveal common usage patterns. Further, a prototype user interface based on elastic lists for browsing by listening context is presented. Indeed several studies indicate that there exist usage patterns that people con- sciously or unconsciously use when they access music collections or describe music: In a user study (14) that analyzed organization and access techniques for personal music collections, several "idiosyncratic genres" could be identified that users tend to use to classify and organize their music. These idiosyncratic genres comply largely with the usage context. Typical examples could be "music for driving (and keeping me awake)", "music for programming" or "music to relax in the evening after a long working day". Further, an analysis of requests at the answering service "Google Answers" 1 in the category "music" (2) revealed that