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Measuring the Semantic Value of Folksonomies

机译:测量愚蠢的语义价值

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Semantic Metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Manual techniques are expensive if they rely on skilled cataloguers, but a possible alternative is to make use of community produced annotations such as those collected in folksonomies. This paper reports on an experiment that we carried out to validate the assumption that folksonomies carry more semantic value than keywords extracted by machines. The experiment has been carried-out in two ways: automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set; and subjectively, by asking a human indexer to evaluate the quality of the generated keywords from both systems. The result of the experiment can be considered as evidence for the rich semantics of folksonomies, demonstrating that folksonomies used in the del.icio.us bookmarking service can be used in the process of generating semantic metadata to annotate web resources.
机译:描述文档含义的语义元数据可以手动或使用信息提取技术进行半自动生产。如果他们依赖熟练的编目师,手动技术很昂贵,而是可能的替代方案是利用社区产生的注释,例如在人类组成符中收集的注释。本文报告了我们进行的实验,以验证对人类组成者携带比机器提取的关键字更多的语义值。实验已经两种方式进行:自动,通过测量obksomic集合和机器生成的关键字集之间的重叠百分比;主观地,通过询问人类索引器来评估来自两个系统的生成关键字的质量。实验结果可以被视为富人组成的富语的证据,展示了Del.Icio.us书签服务中使用的愚蠢物理学可以用于生成语义元数据来注释Web资源的过程中。

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