扩展大众分类法用于图像标记

Roman Kern, M. Granitzer, Viktoria Pammer-Schindler
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引用次数: 20

摘要

由于基于内容的图像检索方法效果不理想,多媒体数据的组织和检索强烈依赖于元数据和自由文本描述。大众分类法,协作创建的元数据集,最近合并并帮助组织网络上的多媒体信息。我们的贡献解决了如何用额外的元数据扩展经典大众分类法的问题。我们还讨论了扩展大众分类法的质量及其在标签推荐中的应用。我们证明了原始民间分类法的一些关系是可以替代的,而另一些关系是唯一的。此外,我们的分析表明,40%的正确标签出现在标签推荐集的前10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending Folksonomies for Image Tagging
Due to the unsatisfactory results of content based image retrieval methods, organisation and retrieval of multimedia data strongly relies on metadata and free text description. Folksonomies, collaboratively created sets of metadata, merged recently and help organising multimedia information on the Web. Our contribution addresses the question how to extend a classical folksonomy with additional metadata. We also discuss the quality of the extended folksonomy and its application for tag recommendation. We show that some relations of the original folksonomies can be replaced while others are unique. In addition our analysis shows, that for 40% the correct tag is in the first 10% of the set of tag recommendations.
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