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Honolulu, Hawaii USA
Dec. 18, 2011 to Dec. 21, 2011
ISBN: 978-0-7695-4607-0
pp: 112-117
ABSTRACT
A scheme for identifying the semantic layers of music-related tags is presented. Arguments are provided why the applications of the tags cannot be effectively pursued without a reasonable understanding of their semantic qualities. The identification scheme consists of a set of filters. The first is related with social consensus, user-count ratio, and n-gram properties of tags. The next relies on look-up functions across multiple databases to determine the probable semantic layer of each tag. Examples of the semantic layers with prevalence rates are given based on application of the scheme to a subset of the Million Song Dataset. Finally, a validation of the results was carried out with an independent, smaller hand-annotated dataset, in which high agreement between the identification provided by the scheme and annotations was found.
INDEX TERMS
musical genre, social tags, semantic layers, music information retrieval
CITATION
Rafael Ferrer, Tuomas Eerola, "Looking Beyond Genres: Identifying Meaningful Semantic Layers from Tags in Online Music Collections", ICMLA, 2011, Machine Learning and Applications, Fourth International Conference on, Machine Learning and Applications, Fourth International Conference on 2011, pp. 112-117, doi:10.1109/ICMLA.2011.89
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