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Relying on Discourse Trees to Extract Medical Ontologies from Text

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Artificial Intelligence (RCAI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12948))

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Abstract

We explore the role of discourse analysis in ontology construction. While extracting candidate phrases to form ontology entries from text, it is important to pay attention to which discourse units these phrases occur in. It turns out that not all discourse units are equal in terms of their contribution to forming ontology entries. We survey text mining and ontology information extraction techniques in medical domain and select the ones where advanced linguistic analysis including the discourse level is leveraged the most to produce a robust and efficient ontology. We evaluate the consistency of the resultant ontology and its role in assuring high search relevance using several real-life medical datasets and prove the importance of introducing discourse information into the ontology construction.

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Notes

  1. 1.

    https://medlineplus.gov/druginfo/meds/a603012.html.

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Author information

Authors and Affiliations

  1. Oracle Inc., Redwood Shores, Redwood City, CA, USA

    Boris Galitsky

  2. National Research University Higher School of Economics, Moscow, Russia

    Dmitry Ilvovsky & Elizaveta Goncharova

Authors
  1. Boris Galitsky
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  2. Dmitry Ilvovsky
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  3. Elizaveta Goncharova
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Corresponding author

Correspondence to Elizaveta Goncharova .

Editor information

Editors and Affiliations

  1. Rostov State Transport University, Rostov-on-Don, Russia

    Sergei M. Kovalev

  2. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  3. Russian Academy of Sciences, Moscow, Russia

    Aleksandr I. Panov

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Galitsky, B., Ilvovsky, D., Goncharova, E. (2021). Relying on Discourse Trees to Extract Medical Ontologies from Text. In: Kovalev, S.M., Kuznetsov, S.O., Panov, A.I. (eds) Artificial Intelligence. RCAI 2021. Lecture Notes in Computer Science(), vol 12948. Springer, Cham. https://doi.org/10.1007/978-3-030-86855-0_15

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  • DOI: https://doi.org/10.1007/978-3-030-86855-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86854-3

  • Online ISBN: 978-3-030-86855-0

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