6533b85bfe1ef96bd12bbe01

RESEARCH PRODUCT

Looking Beyond Genres: Identifying Meaningful Semantic Layers from Tags in Online Music Collections

Rafael FerrerTuomas Eerola

subject

Set (abstract data type)Scheme (programming language)Identification (information)Information retrievalComputer scienceSemantic computingMusic information retrievalSemantic Web Stackcomputercomputer.programming_language

description

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.

yearjournalcountryeditionlanguage
2011-12-012011 10th International Conference on Machine Learning and Applications and Workshops
https://doi.org/10.1109/icmla.2011.89