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  • Automatic Extraction of Poetry from Digitally Scanned Books

    Author(s):
    John Foley (see profile)
    Date:
    2020
    Group(s):
    DH2020
    Subject(s):
    Digital humanities, Digital libraries, Natural language processing (Computer science), Data sets, Open access publishing, Poetry
    Item Type:
    Other
    Tag(s):
    Natural language processing, Open data
    Permanent URL:
    http://dx.doi.org/10.17613/zmyr-0857
    Abstract:
    We present an automatic, learned model for the extraction of poetry from digitally scanned books. This poster highlights our recent work on poetry identification from Internet Archive books and the public resources (code, data and models) that exist as a result. We hope that this is the beginning of deeper and richer research into poetry in the digital humanities because curating custom collections of poetry should be less expensive. Additional information about our approach can be found at the home of our dataset: https://poetry.jjfoley.me.
    Notes:
    Accepted as a Poster to DH2020.
    Metadata:
    xml
    Status:
    Published
    Last Updated:
    3 years ago
    License:
    Attribution-NonCommercial-ShareAlike

    Downloads

    Item Name: pdf dh2020-poster-v3.pdf
      Download View in browser
    Activity: Downloads: 101

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