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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Tong Ruan & Liang Zhao & Yang Li & Haofen Wang & Xu Dong, 2018. "On Evaluating Web-Scale Extracted Knowledge Bases in a Comparative Way," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 14(1), pages 98-120, January.
    • Handle: RePEc:igg:jswis0:v:14:y:2018:i:1:p:98-120
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