利用多面标记来改进大众分类法系统中的搜索

HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media Pub Date : 2010-06-13 DOI:10.1145/1810617.1810684

F. Abel, Ricardo Kawase, D. Krause

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引用次数: 3

摘要

在本文中，我们提出了用于利用附加到可用标签分配的附加上下文信息的大众分类法系统的排名算法。我们在TagMe!系统，Flickr的标记前端，并表明我们的算法，利用类别，空间信息和描述标记分配语义的uri，比不考虑这些上下文信息的FolkRank表现得更好。

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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Leveraging multi-faceted tagging to improve search in folksonomy systems

In this paper we present ranking algorithms for folksonomy systems that exploit additional contextual information attached to tag assignments available. We evaluate the algorithms in the TagMe! system, a tagging front-end for Flickr, and show that our algorithms, which exploit categories, spatial information, and URIs describing the semantics of tag assignments, perform significantly better than the FolkRank that does not consider such contextual information.

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HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media

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