Using Association Rules Mining for Retrieving Genre-Specific Music Files

Retrieving a music file from a large database is a non-trivial task. To support this task, many mechanisms have been developed over the years. However, indexing files remains one of the most popular mechanisms. Several algorithms allow feature extraction from audio signals. Usually, these features are used to describe music content. In this paper, we demonstrate that associations between content-based descriptors can be used as well. We have developed a processing chain which uses association rules mining to find significant relations between content-based descriptors of music files. The significant relations are used to index music files. Experiments conducted demonstrates that the proposed approach can yield interesting results especially with classical music.

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