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Analysing, Representing and Classifying Neuroscience Questions Using Ontologies

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Brain Informatics (BI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12960))

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Abstract

Neuroscience is an important area of research due to the nature of the brain and its diseases. Scientists in this field tend to ask complicated questions which are time-consuming to answer and need several resources. Analysing, representing and finally, classifying these questions assist question resolution systems to be able to tackle them more easily.

To achieve its objectives, this study contains three different tasks, including an ontology-based question analysis approach to find question dimensions for representing questions and shaping categories for them; and two approaches in classifying questions, including one ontology-based and a set of statistical approaches.

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Author information

Authors and Affiliations

  1. University of Melbourne, Melbourne, Australia

    Aref Eshghishargh & Kathleen Gray

Authors
  1. Aref Eshghishargh
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  2. Kathleen Gray
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Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. Jahangirnagar University, Dhaka, Bangladesh

    M Shamim Kaiser

  3. University of Padua, Padua, Italy

    Stefano Vassanelli

  4. Tsinghua University, Beijing, China

    Qionghai Dai

  5. Maebashi Institute of Technology, Maebashi, Japan

    Ning Zhong

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Eshghishargh, A., Gray, K. (2021). Analysing, Representing and Classifying Neuroscience Questions Using Ontologies. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds) Brain Informatics. BI 2021. Lecture Notes in Computer Science(), vol 12960. Springer, Cham. https://doi.org/10.1007/978-3-030-86993-9_24

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  • DOI: https://doi.org/10.1007/978-3-030-86993-9_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86992-2

  • Online ISBN: 978-3-030-86993-9

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