Flickr tag recommendation based on collective knowledge
Flickr tag recommendation based on collective knowledge
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DOI：
10.1145/1367497.1367542
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发表时间：
2008-04
期刊：
影响因子：
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通讯作者：
Börkur Sigurbjörnsson;R. V. Zwol
中科院分区：
文献类型：
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作者：
Börkur Sigurbjörnsson;R. V. Zwol
Flickr和Zooomr等在线照片服务允许用户与家人、朋友和整个在线社区分享他们的照片。这些服务的一个重要方面是用户使用所谓的标签来手动注释他们的照片，这些标签描述了照片的内容或提供了额外的上下文和语义信息。在这篇文章中，我们研究了如何在标记阶段帮助用户。我们的研究贡献是双重的。我们分析了Flickr的一个有代表性的快照，并通过标签特征描述的方式展示了结果，重点是用户如何标记照片以及标签中包含哪些信息。在此基础上，我们提出并评估了标签推荐策略，通过推荐一组可以添加到照片中的标签来支持用户的照片标注任务。实验评估结果表明，对于原始标注穷举程度不同的各种照片，我们可以有效地推荐相关标签。
Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.