On Evaluating Web-Scale Extracted Knowledge Bases in a Comparative Way

Tong Ruan, Liang Zhao, Yang Li, Haofen Wang and Xu Dong
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Tong Ruan: Department of Computer Science & Engineering, East China University of Science & Technology, Shanghai, China
Liang Zhao: Department of Computer Science & Engineering, East China University of Science & Technology, Shanghai, China
Yang Li: Department of Computer Science & Engineering, East China University of Science & Technology, Shanghai, China
Haofen Wang: Department of Computer Science & Engineering, East China University of Science & Technology, Shanghai, China
Xu Dong: Department of Computer Science & Engineering, East China University of Science & Technology, Shanghai, China

International Journal on Semantic Web and Information Systems (IJSWIS), 2018, vol. 14, issue 1, 98-120

Abstract: In this article, the authors design two metric sets considering Richness and Correctness based on a quasi-formal conceptual representation. They also design a novel metric set on overlapped instances of different KBs to make the metric results comparable. Finally, they use random sampling techniques to reduce human efforts for assessing the correctness. The authors evaluate three large Chinese KBs including DBpedia Chinese, Zhishi.me and SSCO comparatively, and further compare them with English KBs in terms of data set qualities. They also compare different versions of DBpedia and YAGO. The findings in these KBs not only give a detailed report of the current situation of extracted KBs, but also show the effectiveness of their methods in assessing the quality of Web-Scale KBs comparatively.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:14:y:2018:i:1:p:98-120

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