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E-SKB: A Semantic Knowledge Base for Emergency

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Book cover Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data (CCKS 2016)

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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.

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Acknowledgments

This work was partly supported by the National Science Foundation of China (No. 61502359), the National Students’ Innovative Entrepreneurship Training Program under Grant (No. 201510488016).

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Correspondence to Yu Liu .

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© 2016 Springer Nature Singapore Pte Ltd.

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Wen, C., Liu, Y., Gu, J., Chen, J., Zhang, Y. (2016). E-SKB: A Semantic Knowledge Base for Emergency. In: Chen, H., Ji, H., Sun, L., Wang, H., Qian, T., Ruan, T. (eds) Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data. CCKS 2016. Communications in Computer and Information Science, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-10-3168-7_19

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  • DOI: https://doi.org/10.1007/978-981-10-3168-7_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3167-0

  • Online ISBN: 978-981-10-3168-7

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