Abstract
This paper develops and applies sequential pattern mining to a corpus of songs for the bagana, a large lyre played in Ethiopia. An important aspect of this repertoire is the unique availability of rare motifs that have been used by a master bagana teacher in Ethiopia. The method is applied to find antipatterns: patterns that are surprisingly rare in a corpus of bagana songs. In contrast to previous work, this is performed without an explicit set of background pieces. The results of this study show that data mining methods can reveal with high significance these antipatterns of interest based on the computational analysis of a small corpus of bagana songs.
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Conklin, D., Weisser, S. (2014). Antipattern Discovery in Ethiopian Bagana Songs. In: Džeroski, S., Panov, P., Kocev, D., Todorovski, L. (eds) Discovery Science. DS 2014. Lecture Notes in Computer Science(), vol 8777. Springer, Cham. https://doi.org/10.1007/978-3-319-11812-3_6
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DOI: https://doi.org/10.1007/978-3-319-11812-3_6
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