Semantic Wikipedia

IF 2.1 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Max Völkel, M. Krötzsch, Denny Vrandečić, H. Haller, R. Studer
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引用次数: 208

Abstract

Wikipedia is the world's largest collaboratively edited source of encyclopaedic knowledge. But in spite of its utility, its contents are barely machine-interpretable. Structural knowledge, e.,g. about how concepts are interrelated, can neither be formally stated nor automatically processed. Also the wealth of numerical data is only available as plain text and thus can not be processed by its actual meaning.We provide an extension to be integrated in Wikipedia, that allows the typing of links between articles and the specification of typed data inside the articles in an easy-to-use manner.Enabling even casual users to participate in the creation of an open semantic knowledge base, Wikipedia has the chance to become a resource of semantic statements, hitherto unknown regarding size, scope, openness, and internationalisation. These semantic enhancements bring to Wikipedia benefits of today's semantic technologies: more specific ways of searching and browsing. Also, the RDF export, that gives direct access to the formalised knowledge, opens Wikipedia up to a wide range of external applications, that will be able to use it as a background knowledge base.In this paper, we present the design, implementation, and possible uses of this extension.
语义维基百科
维基百科是世界上最大的协同编辑的百科知识来源。但是,尽管它很实用,但它的内容几乎是机器无法解释的。结构知识,例如:关于概念是如何相互关联的,既不能正式陈述,也不能自动处理。此外,大量的数值数据只能以纯文本形式提供,因此不能按其实际含义进行处理。我们提供了一个扩展集成在维基百科,它允许键入文章之间的链接和文章内的类型化数据的规范在一个易于使用的方式。即使是普通用户也可以参与创建一个开放的语义知识库,维基百科有机会成为语义陈述的资源,其规模、范围、开放性和国际化程度迄今为止都是未知的。这些语义增强为维基百科带来了当今语义技术的好处:更具体的搜索和浏览方式。此外,RDF导出,它提供了对形式化知识的直接访问,将维基百科开放给广泛的外部应用程序,这些应用程序将能够将其用作背景知识库。在本文中,我们介绍了该扩展的设计、实现和可能的用途。
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来源期刊
Journal of Web Semantics
Journal of Web Semantics 工程技术-计算机:人工智能
CiteScore
6.20
自引率
12.00%
发文量
22
审稿时长
14.6 weeks
期刊介绍: The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.
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