Limitations of interactive music recommendation based on audio content

Authors:
Arthur Flexer;Martin Gasser;Dominik Schnitzer
Affiliations:
Austrian Research Institute for Artificial Intelligence, Vienna, Austria;Austrian Research Institute for Artificial Intelligence, Vienna, Austria;Johannes Kepler University, Linz, Austria
Venue:
Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction with Sound
Year:
2010

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Abstract

We present a study on the limitations of an interactive music recommendation service based on automatic computation of audio similarity. Songs which are, according to the audio similarity function, similar to very many other songs and hence appear unwantedly often in recommendation lists keep a significant proportion of the audio collection from being recommended at all. This problem is studied in-depth with a series of computer experiments including analysis of alternative audio similarity functions and comparison with actual download data.