Mining contour sequences for significant closed patterns. Conklin, D. Journal of Mathematics and Music, 0(0):1–13, Taylor & Francis, 2021. Paper doi abstract bibtex Sequential pattern mining in music is a central part of automated music analysis and music generation. This paper evaluates sequential pattern mining on a corpus of Mozarabic chant neume sequences that have been annotated by a musicologist with intra-opus patterns. Significant patterns are discovered in three settings: all closed patterns, maximal closed patterns, and minimal closed patterns. Each setting is evaluated against the annotated patterns using the measures of recall and precision. The results indicate that it is possible to retrieve all known patterns with an acceptable precision using significant closed pattern discovery.
@Article{ conklin2021-mining,
author = {Conklin, Darrell},
year = {2021},
title = {Mining contour sequences for significant closed
patterns},
abstract = {Sequential pattern mining in music is a central part of
automated music analysis and music generation. This paper
evaluates sequential pattern mining on a corpus of
Mozarabic chant neume sequences that have been annotated
by a musicologist with intra-opus patterns. Significant
patterns are discovered in three settings: all closed
patterns, maximal closed patterns, and minimal closed
patterns. Each setting is evaluated against the annotated
patterns using the measures of recall and precision. The
results indicate that it is possible to retrieve all known
patterns with an acceptable precision using significant
closed pattern discovery.},
doi = {10.1080/17459737.2021.1903591},
journal = {Journal of Mathematics and Music},
keywords = {music contour},
mendeley-tags= {music contour},
number = {0},
pages = {1--13},
publisher = {Taylor \& Francis},
url = {https://doi.org/10.1080/17459737.2021.1903591},
volume = {0}
}
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