超越体裁:从在线音乐收藏的标签中识别有意义的语义层

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI:10.1109/ICMLA.2011.89

R. Ferrer, T. Eerola

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引用次数: 3

摘要

提出了一种识别音乐相关标签语义层的方案。在没有对标签语义质量的合理理解的情况下，为什么标签的应用不能有效地进行论证。该识别方案由一组过滤器组成。第一个与社会共识、用户计数比率和标签的n-gram属性有关。下一个依赖于跨多个数据库的查找函数来确定每个标记的可能语义层。基于该方案在百万首歌曲数据集子集上的应用，给出了具有流行率的语义层示例。最后，用一个独立的、较小的手工标注数据集对结果进行验证，发现该方案提供的识别与标注之间的一致性很高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2011 10th International Conference on Machine Learning and Applications and Workshops

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