Sequence-Based Extractive Summarisation for Scientific Articles

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


    This paper presents the results of research on supervised extractive
    text summarisation for scientific articles. We show that a simple
    sequential tagging model based only on the text within a document achieves high results against a simple classification model.
    Improvements can be achieved through additional sentence-level
    features, though these were minimal. Through further analysis, we
    show the potential of the sequential model relying on the structure
    of the document depending on the academic discipline which the
    document is from
    Original languageAmerican English
    Title of host publicationSci-K 2022
    PublisherAssociation for Computing Machinery
    ISBN (Electronic)978-1-4503-9130-6/22/04
    ISBN (Print)978-1-4503-9130-6/22/04
    StatePublished - 2022

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