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Extracting Knowledge Claims for Automatic Evidence Synthesis Using Semantic Technology

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Book cover Knowledge Engineering and Knowledge Management (EKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10180))

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Abstract

Systematic review, a form of evidence synthesis that critically appraises existing studies on the same topic and synthesizes study results, helps reduce the evidence gap. However, keeping the systematic review up-to-date is a great challenge partly due to the difficulty in interpreting the conclusion of a systematic review. A promising approach to this challenge is to make semantic representation of the claims made in both the systematic review and the included studies it synthesizes so that it’s possible to automatically predict whether the conclusion of a systematic review changes given a new study. In this dissertation work, we developed a taxonomy to represent knowledge claims both in systematic review and its included studies with the goal of automatically updating a systematic review. We then developed machine learning models to automatically predict a synthesized claim from claims in individual studies.

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Acknowledgement

The author would like to thank Professor Catherine Blake and Professor Jodi Schneider for their guidance and support in writing this paper.

Author information

Authors and Affiliations

  1. School of Information Sciences, University of Illinois at Urbana-Champaign, Champaign, USA

    Jinlong Guo

Authors
  1. Jinlong Guo
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Corresponding author

Correspondence to Jinlong Guo .

Editor information

Editors and Affiliations

  1. University of Bologna , Bologna, Italy

    Paolo Ciancarini

  2. University of Bologna , Bologna, Italy

    Francesco Poggi

  3. Stanford University , Palo Alto, California, USA

    Matthew Horridge

  4. Lancaster University , Lancaster, United Kingdom

    Jun Zhao

  5. Garvan Institute of Medical Research , Darlinghurst, New South Wales, Australia

    Tudor Groza

  6. Universidad Politecnica de Madrid , Boadilla del Monte, Spain

    Mari Carmen Suarez-Figueroa

  7. The Open University , Milton Keynes, United Kingdom

    Mathieu d'Aquin

  8. STLab ISTC-CNR , Rome, Italy

    Valentina Presutti

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Guo, J. (2017). Extracting Knowledge Claims for Automatic Evidence Synthesis Using Semantic Technology. In: Ciancarini, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10180. Springer, Cham. https://doi.org/10.1007/978-3-319-58694-6_37

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  • DOI: https://doi.org/10.1007/978-3-319-58694-6_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58693-9

  • Online ISBN: 978-3-319-58694-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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