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基于实例的叙词表与民俗学映射

Instanced-based mapping between thesauri and folksonomies
课程网址: http://videolectures.net/iswc08_wartena_ibm/  
主讲教师: Christian Wartena
开课单位: 远程通信研究所
开课时间: 2008-11-24
课程语种: 英语
中文简介:
用户可以对项目进行注释的基于Web的系统的出现提出了源于协作注释过程(通常称为民俗分类法)和以更传统方式分配的关键词的词汇表之间的语义互操作性问题。如果根据两个系统注释集合,例如通过标签和关键字,带注释的数据可用于基于实例的词汇表之间的映射。这种匹配的基础是概念之间的适当相似性度量,基于它们作为注释的分布。在本文中,我们提出了一种新的相似性度量,它可以利用用户生成的元数据的一些特殊属性。我们使用来自维基百科的一组文章评估了这一度量,这些文章都根据维基百科的主题结构进行分类,并由书签服务del.icio.us的用户进行注释。使用新测量的结果明显优于使用在文献中为该任务提出的标准相似性测量获得的结果,即,它与人类判断更好地相关。我们认为该措施还具有基于例如更传统开发的词汇表的映射的益处。
课程简介: The emergence of web based systems in which users can annotate items, raises the question of the semantic interoperability between vocabularies originating from collaborative annotation processes, often called folksonomies, and keywords assigned in a more traditional way. If collections are annotated according to two systems, e.g. with tags and keywords, the annotated data can be used for instance based mapping between the vocabularies. The basis for this kind of matching is an appropriate similarity measure between concepts, based on their distribution as annotations. In this paper we propose a new similarity measure that can take advantage of some special properties of user generated metadata. We have evaluated this measure with a set of articles from Wikipedia which are both classified according to the topic structure of Wikipedia and annotated by users of the bookmarking service del.icio.us. The results using the new measure are significantly better than those obtained using standard similarity measures proposed for this task in the literature, i.e., it correlates better with human judgments. We argue that the measure also has benefits for instance based mapping of more traditionally developed vocabularies.
关 键 词: Web; 协作注释; 元数据
课程来源: 视频讲座网
最后编审: 2019-05-05:lxf
阅读次数: 29