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On Publishing Chinese Linked Open Schema

机译:关于发布中文链接的开放式架构

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Linking Open Data (LOD) is the largest community effort for semantic data publishing which converts the Web from a Web of document to a Web of interlinked knowledge. While the state of the art LOD contains billion of triples describing millions of entities, it has only a limited number of schema information and is lack of schema-level axioms. To close the gap between the lightweight LOD and the expressive ontologies, we contribute to the complementary part of the LOD, that is, Linking Open Schema (LOS). In this paper, we introduce Zhishi.schema, the first effort to publish Chinese linked open schema. We collect navigational categories as well as dynamic tags from more than 50 various most popular social Web sites in China. We then propose a two-stage method to capture equivalence, subsumption and relate relationships between the collected categories and tags, which results in an integrated concept taxonomy and a large semantic network. Experimental results show the high quality of Zhishi.schema. Compared with category systems of DB-pedia, Yago, BabelNet, and Preebase, Zhishi.schema has wide coverage of categories and contains the largest number of subsumptions between categories. When substituting Zhishi.schema for the original category system of Zhishi.me, we not only filter out incorrect category subsumptions but also add more finer-grained categories.
机译:链接开放数据(LOD)是用于语义数据发布的最大的社区工作,它可以将Web从文档Web转换为相互链接的知识Web。虽然最先进的LOD包含数十亿个描述了数百万个实体的三元组,但是它只有有限数量的模式信息,并且缺少模式级公理。为了缩小轻量级LOD与表达本体之间的差距,我们对LOD的补充部分做出了贡献,即链接开放模式(LOS)。在本文中,我们将介绍Zhishi.schema,这是发布中文链接的开放式架构的第一个尝试。我们从中国50多个最受欢迎的社交网站上收集导航类别和动态标签。然后,我们提出了一种两阶段的方法来捕获等效,包含和关联所收集的类别和标签之间的关系,从而形成一个集成的概念分类法和一个大型语义网络。实验结果表明,Zhishi.schema具有较高的质量。与DB-pedia,Yago,BabelNet和Preebase的类别系统相比,Zhishi.schema具有广泛的类别覆盖范围,并且包含类别之间最多的引用。当用Zhishi.schema代替Zhishi.me的原始类别系统时,我们不仅过滤掉了错误的类别包含,而且添加了更细粒度的类别。

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