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Erschienen in:
2016 | OriginalPaper | Buchkapitel
E-SKB: A Semantic Knowledge Base for Emergency
verfasst von : Chang Wen, Yu Liu, Jinguang Gu, Jing Chen, Yingping Zhang
Erschienen in: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data
Verlag: Springer Singapore
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Abstract
Although the number of knowledge bases in Linked Open Data has grown explosively, there are few knowledge bases about emergency, an important issue in the area of social management. In this paper, we introduce a semantic knowledge base of emergency, extracted from an authoritative website. According to the characteristics of the website, a framework is suggested to convert web into RDF. In order to help researchers acquire more knowledge, we follow the publishing rules of Linked Open Data—not only using URIs to label the objects in the semantic knowledge base, but also providing links to DBpedia. Finally, we employ Sesame to store and publish the semantic knowledge base, and develop a query interface to retrieve the knowledge base with SPARQL.